Publications

Thought-Provoking Research from our Training Centre

2024
An introduction to quantum computing for statisticians and data scientists

Anna Lopatnikova, Minh-Ngoc Tran, Scott A. Sisson
Foundations of Data Science, Volume 6, Issue 3, September 2024; https://doi.org/10.3934/fods.2024013

Cooperative geophysical inversion integrated with 3-D geological modelling in the Boulia region, QLD

Mahtab Rashidifard, Jérémie Giraud, Mark Lindsay, Mark Jessell
Geophysical Journal International, Volume 238, Issue 2, August 2024; https://doi.org/10.1093/gji/ggae179

Bayesian neural networks via MCMC: a Python-based tutorial

Rohitash Chandra, Joshua Simmons
IEEE Access, May 2024; https://doi.org/10.1109/ACCESS.2024.3401234

Opinion Mining by Convolutional Neural Networks for Maximizing Discoverability of Nanomaterials

Tong Xie, Yuwei Wan, Haoran Wang, Ina Østrøm, Shaozhou Wang, Mingrui He, Rong Deng, Xinyuan Wu, Clara Grazian, Chunyu Kit and Bram Hoex
Journal of Chemical Information and Modeling, Volume 64, Issue 7, May 2024; https://doi.org/10.1021/acs.jcim.3c00746

Physiography, foraging mobility, and the first peopling of Sahul

Tristan Salles, Renaud Joannes-Boyau, Ian Moffat, Laurent Husson & Manon Lorcery
Nature Communications, Volume 15, April 2024; https://doi.org/10.1038/s41467-024-47662-1

Spatio-Temporal Stick-Breaking Process

Clara Grazian
Bayesian Analysis, March 2024; https://doi.org/10.1214/24-BA1419

A systematic review of climate change science relevant to Australian design flood estimation

Conrad Wasko, Seth Westra, Rory Nathan, Acacia Pepler, Timothy H. Raupach, Andrew Dowdy, Fiona Johnson, Michelle Ho, Kathleen L. McInnes, Doerte Jakob, Jason Evans, Gabriele Villarini, and Hayley J. Fowler
Hydrology and Earth System Sciences
, Volume 28, Issue 5, March 2024; https://doi.org/10.5194/hess-28-1251-2024

Creation of a structured solar cell material dataset and performance prediction using large language models

Tong Xie, Yuwei Wan, Yufei Zhou, Wei Huang, Yixuan Liu, Qingyuan Linghu, Shaozhou Wang, Chunyu Kit, Clara Grazian, Wenjie Zhang, Bram Hoex
Patterns
, Volume 5, Issue 5, March 2024; https://doi.org/10.1016/j.patter.2024.100955

Agricultural water accounting: Complementing a governance monitoring schema with remote sensing calculations at different scales

Ignacio Fuentes, R. Willem Vervoort, James McPhee, Luis A. Reyes Rojas
Agricultural Water Management, Volume 292, March 2024; https://doi.org/10.1016/j.agwat.2024.108676

A unified machine learning framework for basketball team roster construction: NBA and WNBA

Yuhao Ke, Ranran Bian, Rohitash Chandra
Applied Soft Computing, Volume 153, March 2024; https://doi.org/10.1016/j.asoc.2024.111298

A Bayesian hierarchical model for the inference between metal grade with reduced variance: Case studies in porphyry Cu deposits

Yufu Niu, Mark Lindsay, Peter Coghill, Richard Scalzo, Lequn Zhang
Geoscience Frontiers, Volume 15, Issue 2, March 2024; https://doi.org/10.1016/j.gsf.2023.101767

Development and application of feature engineered geological layers for ranking magmatic, volcanogenic, and orogenic system components in Archean greenstone belts

R.M. Montsion, S. Perrouty, M.D. Lindsay, M.W. Jessell, R. Sherlock
Geoscience Frontiers, Volume 15, Issue 2, March 2024; https://doi.org/10.1016/j.gsf.2023.101759

Remote sensing of water colour in small southeastern Australian waterbodies

Shuang Liu, Seokhyeon Kim, William Glamore, Bojan Tamburic, Fiona Johnson
Journal of Environmental Management, Volume 352, February 2024; https://doi.org/10.1016/j.jenvman.2024.120096

Integrated catchment models for policy development and decision making

R. Willem Vervoort, Eliana Nervi, Walter Baethgen
Agrociencia Uruguay, Volume 27, February 2024; https://doi.org/10.31285/AGRO.27.1194

Mitigating uncertainties in mineral exploration targeting: Majority voting and confidence index approaches in the context of an exploration information system (EIS)

Mahyar Yousefi, Mark D. Lindsay, Oliver Kreuzer
Ore Geology Reviews, Volume 165, February 2024; https://doi.org/10.1016/j.oregeorev.2024.105930

Water Market Functionality: Evidence From the Australian Experience

Maruge Zhao, Tiho Ancev, R. Willem Vervoort
Water Resources Research, Volume 60, Issue 2, February 2024; https://doi.org/10.1029/2022WR033938

Assessing the relative importance of dry-season incoming solar radiation and water storage dynamics during the 2005, 2010 and 2015 southern Amazon droughts: not all droughts are created equal

Shuang Liu, Tim R McVicar, Xue Wu, Xin Cao and Yi Liu
Environmental Research Letters, Volume 19, Issue 3, February 2024; https://doi.org/10.1088/1748-9326/ad281e

Sequential reversible jump MCMC for dynamic Bayesian neural networks

Nhat Minh Nguyen, Minh-Ngoc Tran, Rohitash Chandra
Neurocomputing, Volume 564, January 2024; https://doi.org/10.1016/j.neucom.2023.126960

Global evapotranspiration models and their performance at different spatial scales: Contrasting a latitudinal gradient against global catchments

Ignacio Fuentes, R. Willem Vervoort, James McPhee
Journal of Hydrology, Volume 628, January 2024; https://doi.org/10.1016/j.jhydrol.2023.130477

Stochastic variational inference for GARCH models

Hanwen Xuan, Luca Maestrini, Feng Chen, Clara Grazian
Statistics and Computing, Volume 34, 2024; https://doi.org/10.1007/s11222-023-10356-7

2023
ReefCoreSeg: A clustering-based framework for multi-source data fusion for segmentation of reef cores

Ratneel Deo, Jody M. Webster, Tristan Salles, Rohitash Chandra
IEEE Access, December 2023; https://doi.org/10.1109/ACCESS.2023.3341156

Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources

Haotian Zheng, Qizhou Wang, Zhen Fang, Xiaobo Xia, Feng Liu, Tongliang Liu, Bo Han
arXiv preprint, December 2023; https://doi.org/10.48550/arXiv.2311.03236

Landscape dynamics and the Phanerozoic diversification of the biosphere

Tristan Salles, Laurent Husson, Manon Lorcery, Beatriz Hadler Boggiani
Nature, November 2023; https://doi.org/10.1038/s41586-023-06777-z

DeepGR4J: A deep learning hybridization approach for conceptual rainfall-runoff modelling

Arpit Kapoor, Sahani Pathiraja, Lucy Marshall, Rohitash Chandra
Environmental Modelling & Software, Volume 169, November 2023; https://doi.org/10.1016/j.envsoft.2023.105831

Opinion Mining by Convolutional Neural Networks for Maximizing Discoverability of Nanomaterials

Tong Xie, Yuwei Wan, Haoran Wang, Ina Østrøm, Shaozhou Wang, Mingrui He, Rong Deng, Xinyuan Wu, Clara Grazian, Chunyu Kit, Bram Hoex
Journal of Chemical Information and Modeling, November 2023; https://doi.org/10.1021/acs.jcim.3c00746

Tractable skew-normal approximations via matching

Jackson Zhou, Clara Grazian, John T. Ormerod
Journal of Statistical Computation and Simulation, November 2023; https://doi.org/10.1080/00949655.2023.2277885

Influence of resampling techniques on Bayesian network performance in predicting increased algal activity

Maryam Zeinolabedini Rezaabad, Heather Lacey, Lucy Marshall, Fiona Johnson
Water Research, Volume 244, October 2023; https://doi.org/10.1016/j.watres.2023.120558

Fast Expectation Propagation for Heteroscedastic, Lasso-Penalized, and Quantile Regression

Jackson Zhou, John T. Ormerod, Clara Grazian
Journal of Machine Learning Research, Volume 24, October 2023; https://www.jmlr.org/papers/v24/23-0104.html

Effects of pressure on the structure of partially premixed turbulent diffusion flames: Calculations using MMC-LES

Saeed Aldawsari, Sebastian Galindo-Lopez, Matthew J. Cleary, Assaad R. Masri
Combustion and Flame, Volume 256, October 2023; https://doi.org/10.1016/j.combustflame.2023.112991

InstanT: Semi-supervised Learning with Instance-dependent Thresholds

Muyang Li, Runze Wu, Haoyu Liu, Jun Yu, Xun Yang, Bo Han, Tongliang Liu
arXiv preprint, October 2023; https://doi.org/10.48550/arXiv.2310.18910

FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness for Semi-Supervised Learning

Zhuo Huang, Li Shen, Jun Yu, Bo Han, Tongliang Liu
arXiv preprint, October 2023; https://doi.org/10.48550/arXiv.2310.16412

Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation

Jianing Zhu, Geng Yu, Jiangchao Yao, Tongliang Liu, Gang Niu, Masashi Sugiyama, Bo Han
arXiv preprint, October 2023; https://doi.org/10.48550/arXiv.2310.13923

FedFed: Feature Distillation against Data Heterogeneity in Federated Learning

Zhiqin Yang, Yonggang Zhang, Yu Zheng, Xinmei Tian, Hao Peng, Tongliang Liu, Bo Han
arXiv preprint, October 2023; https://doi.org/10.48550/arXiv.2310.05077

PADDLES: Phase-Amplitude Spectrum Disentangled Early Stopping for Learning with Noisy Labels

Huaxi Huang, Hui Kang, Sheng Liu, Olivier Salvado, Thierry Rakotoarivelo, Dadong Wang, Tongliang Liu
Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023

Combating Noisy Labels with Sample Selection by Mining High-Discrepancy Examples

Xiaobo Xia, Bo Han, Yibing Zhan, Jun Yu, Mingming Gong, Chen Gong, Tongliang Liu
Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023

Late Stopping: Avoiding Confidently Learning from Mislabeled Examples

Suqin Yuan, Lei Feng, Tongliang Liu
Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023

Holistic Label Correction for Noisy Multi-Label Classification

Xiaobo Xia, Jiankang Deng, Wei Bao, Yuxuan Du, Bo Han, Shiguang Shan, Tongliang Liu
Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023

Robust Generalization Against Photon-Limited Corruptions via Worst-Case Sharpness Minimization

Zhuo Huang, Miaoxi Zhu, Xiaobo Xia, Li Shen, Jun Yu, Chen Gong, Bo Han, Bo Du, Tongliang Liu
Proceedings of the IEEE/CVF International Conference on Computer Vision and Pattern Recognition (CVPR), 2023

Examining past and projecting future: an 800-year streamflow reconstruction of the Australian Murray river

P A Higgins, J G Palmer, M S Andersen, C S M Turney, F Johnson, K Allen, D Verdon-Kidd, E R Cook
Environmental Research Letters, Volume 18, September 2023; https://doi.org/10.1088/1748-9326/acf8d9

HumanMAC: Masked Motion Completion for Human Motion Prediction

Ling-Hao Chen, Jiawei Zhang, Yewen Li, Yiren Pang, Xiaobo Xia, Tongliang Liu
arXiv preprint, August 2023; https://doi.org/10.48550/arXiv.2302.03665

Exploring Model Misspecification in Statistical Finite Elements via Shallow Water Equations

Connor Duffin, Paul Branson, Matt Rayson, Mark Girolami, Edward Cripps, Thomas Stemler
arXiv preprint, July 2023; https://doi.org/10.48550/arXiv.2307.05334

Non-stationarity in extreme rainfalls across Australia

Lalani Jayaweera, Conrad Wasko, Rory Nathan, Fiona Johnson
Journal of Hydrology
, Volume 624, September 2023; https://doi.org/10.1016/j.jhydrol.2023.129594

Extreme events in the multi-proxy South Pacific drought atlas

Philippa Higgins, Jonathan Palmer, Martin Andersen, Christian Turney, Fiona Johnson
Climatic Change, Volume 176, July 2023; https://doi.org/10.1007/s10584-023-03585-2

An application of copulas to OPEC’s changing influence on fossil fuel prices

Clara Grazian, A. McInnes
Econometric Reviews, Volume 42, July 2023; https://doi.org/10.1080/07474938.2023.2222637

Do Derived Drought Indices Better Characterize Future Drought Change?

Ze Jiang, Fiona Johnson, Ashish Sharma
Earth’s Future
, Volume 11, Issue 7, July 2023; https://doi.org/10.1016/j.jhydrol.2023.129594

Adaptively switching between a particle marginal Metropolis-Hastings and a particle Gibbs kernel in SMC(2)

Imke Botha, Robert Kohn, Leah South, Christopher Drovandi
arXiv preprint, July 2023; https://doi.org/10.48550/arXiv.2307.11553

A review of globally available data sources for modelling the Water-Energy-Food Nexus

Jack Lodge, Andrew Dansie, Fiona Johnson
Earth-Science Reviews
, Volume 243, August 2023; https://doi.org/10.1016/j.jhydrol.2023.129594

Automatically adapting the number of state particles in SMC(2)

Imke Botha, Robert Kohn, Leah South & Christopher Drovandi
Statistics and Computing, Volume 33, May 2023; https://doi.org/10.1007/s11222-023-10250-2

A New Method for Postprocessing Numerical Weather Predictions Using Quantile Mapping in the Frequency Domain

Ze Jiang, Fiona Johnson
Monthly Weather Review
, April 2023; https://doi.org/10.1016/j.jhydrol.2023.129594

Large Language Models as Master Key: Unlocking the Secrets of Materials Science with GPT

Tong Xie, Yuwei Wan, Wei Huang, Yufei Zhou, Yixuan Liu, Qingyuan Linghu, Shaozhou Wang, Chunyu Kit, Clara Grazian, Wenjie Zhang, Bram Hoex
arXiv preprint, April 2023; https://doi.org/10.48550/arXiv.2304.02213

Particle Mean Field Variational Bayes

Minh-Ngoc Tran, Paco Tseng, Robert Kohn
arXiv preprint, May 2023; https://doi.org/10.48550/arXiv.2303.13930

Wasserstein Gaussianization and Efficient Variational Bayes for Robust Bayesian Synthetic Likelihood

Nhat-Minh Nguyen, Minh-Ngoc Tran, Christopher Drovandi, David Nott
arXiv preprint, May 2023; https://doi.org/10.48550/arXiv.2305.14746

Verifying model performance using validation of Pareto solutions

N. Harvey, L. Marshall, R.W. Vervoort
Journal of Hydrology
, Volume 621, June 2023; https://doi.org/10.1016/j.jhydrol.2023.129594

Cyclone trajectory and intensity prediction with uncertainty quantification using variational recurrent neural networks

Arpit Kapoor, Anshul Negi, Lucy Marshall, Rohitash Chandra
Environmental Modelling & Software, Volume 162, April 2023; https://doi.org/10.1016/j.envsoft.2023.105654

Bayesian neural networks via MCMC: a Python-based tutorial

Rohitash Chandra, Royce Chen, Joshua Simmons
arXiv preprint, April 2023; https://doi.org/10.48550/arXiv.2304.02595

Harnessing Out-Of-Distribution Examples via Augmenting Content and Style

Zhuo Huang, Xiaobo Xia, Li Shen, Bo Han, Mingming Gong, Chen Gong, Tongliang Liu
arXiv preprint, April 2023; https://doi.org/10.48550/arXiv.2207.03162

Combating Exacerbated Heterogeneity for Robust Models in Federated Learning

Jianing Zhu, Jiangchao Yao, Tongliang Liu, Quanming Yao, Jianliang Xu, Bo Han
arXiv preprint, March 2023; https://doi.org/10.48550/arXiv.2303.00250

Spatio-temporal stick-breaking process

Clara Grazian
arXiv preprint, March 2023; https://doi.org/10.48550/arXiv.2303.17177

Hundred million years of landscape dynamics from catchment to global scale

Tristan Salles, Laurent Husson, Patrice Rey, Claire Mallard, Sabin Zahirovic, Beatriz Hadler Boggiani, Nicolas Coltice, Maëlis Arnould
SCIENCE, Vol 379, Issue 6635; https://doi.org/10.1126/science.add2541

Copula modelling with penalized complexity priors: the bivariate case

Diego Battagliese, Clara Grazian, Brunero Liseo & Cristiano Villa
TEST, 2023; https://doi.org/10.1007/s11749-022-00843-w

Out-of-distribution Detection with Implicit Outlier Transformation

Qizhou Wang, Junjie Ye, Feng Liu, Quanyu Dai, Marcus Kalander, Tongliang Liu, Jianye Hao, Bo Han
arXiv preprint, March 2023; https://doi.org/10.48550/arXiv.2303.05033

Structured variational approximations with skew normal decomposable graphical models

Robert Salomone, Xuejun Yu, David J. Nott, Robert Kohn
arXiv preprint, February 2023; https://doi.org/10.48550/arXiv.2302.03348

A holistic view of label noise transition matrix in deep learning and beyond

Yong Lin, Renjie Pi, Weizhong Zhang, Xiaobo Xia, Jiahui Gao, Xiao Zhou, Tongliang Liu, Bo Han
Proceedings of the ICLR 2023 Conference, 2023

Moderate coreset: A universal method of data selection for real-world data-efficient deep learning

Xiaobo Xia, Jiale Liu, Jun Yu, Xu Shen, Bo Han, Tongliang Liu
Proceedings of the ICLR 2023 Conference, 2023

Mosaic Representation Learning for Self-supervised Visual Pre-training

Zhaoqing Wang, Ziyu Chen, Yaqian Li, Yandong Guo, Jun Yu, Mingming Gong, Tongliang Liu
Proceedings of the ICLR 2023 Conference, 2023

KRADA: Known-region-aware Domain Alignment for Openset Domain Adaptation in Semantic Segmentation

Chenhong Zhou, Feng Liu, Chen Gong, Rongfei Zeng, Tongliang Liu, William Cheung, Bo Han
Transactions on Machine Learning Research, February 2023; https://openreview.net/forum?id=5II12ypVQo

Skew-Normal Posterior Approximations

Jackson Zhou, Clara Grazian, John Ormerod
arXiv preprint, February 2023; https://doi.org/10.48550/arXiv.2302.08614

FedDAG: Federated DAG Structure Learning

Erdun Gao, Junjia Chen, Li Shen, Tongliang Liu, Mingming Gong, Howard Bondell
arXiv preprint, January 2023; https://doi.org/10.48550/arXiv.2112.03555

The co-determination of home and workplace relocation durations using survival copula analysis

Maryam Bostanara, Taha Hossein Rashidi, Nazmul Arefin Khan, Joshua Auld, Milad Ghasri, Clara Grazian
Computers, Environment and Urban Systems, Volume 99, January 2023; https://doi.org/10.1016/j.compenvurbsys.2022.10189

Utilisation of probabilistic magnetotelluric modelling to constrain magnetic data inversion: proof-of-concept and field application

Jérémie Giraud, Hoël Seillé, Mark D. Lindsay, Gerhard Visser, Vitaliy Ogarko, Mark W. Jessell
Solid Earth, Volume 14, January 2023; https://doi.org/10.5194/se-14-43-2023

2022
Remote sensing to detect harmful algal blooms in inland waterbodies

Shuang Liu, William Glamore, Bojan Tamburic, Abigail Morrow, Fiona Johnson
Science of The Total Environment, Vol. 851, Part 1, December 2022; https://doi.org/10.1016/j.scitotenv.2022.158096

Estimating Noise Transition Matrix with Label Correlations for Noisy Multi-Label Learning

Shikun Li, Xiaobo Xia, Hansong Zhang, Yibing Zhan, Shiming Ge, Tongliang Liu
Proceedings of the 39th International Conference on Machine Learning, 2022

Assessing the impact of conceptual mineral systems uncertainty on prospectivity predictions

Mark D. Lindsay, Agnieszka M. Piechocka, Mark W Jessell, Richard Scalzo, Jeremie Giraud, Guillaume Pirot, Edward Cripps
Geoscience Frontiers, Vol. 13, Issue 6, November 2022; https://doi.org/10.1016/j.gsf.2022.101435

Bayesian neuroevolution using distributed swarm optimization and tempered MCMC

Arpit Kapoor, Eshwar Nukala, Rohitash Chandra
Applied Soft Computing, Vol. 129, Issue 6, November 2022; https://doi.org/10.1016/j.asoc.2022.109528

Towards Lightweight Black-Box Attacks against Deep Neural Networks

Chenghao Sun, Yonggang Zhang, Wan Chaoqun, Qizhou Wang, Ya Li, Tongliang Liu, Bo Han, Xinmei Tian
Proceedings of the 39th International Conference on Machine Learning, 2022; https://doi.org/10.48550/arXiv.2209.14826

Preserved intercratonic lithosphere reveals Proterozoic assembly of Australia

Yongjun Lu, Michael T.D. Wingate, Robert H. Smithies, Klaus Gessner, Simon P. Johnson, Anthony I.S. Kemp, David E. Kelsey, Peter W. Haines, David McB. Martin, Laure Martin, Mark Lindsay
Geology, Vol. 50, Issue 10, August 2022; https://doi.org/10.1130/G50256.1

Sedimentary basins reduce stability of Antarctic ice streams through groundwater feedbacks

Lu Li, Alan R. A. Aitken, Mark D. Lindsay, and Bernd Kulessa
Nature Geoscience, 15, 645–650, 2022; https://doi.org/10.1038/s41561-022-00992-5

Estimating instance-dependent bayes-label transition matrix using a deep neural network

Shuo Yang, Erkun Yang, Bo Han, Yang Liu, Min Xu, Gang Niu, Tongliang Liu
Proceedings of the 39th International Conference on Machine Learning, 2022; https://doi.org/10.48550/arXiv.2105.13001

Modeling Adversarial Noise for Adversarial Training

Dawei Zhou, Nannan Wang, Bo Han, Tongliang Liu
Proceedings of the 39th International Conference on Machine Learning, 2022; https://doi.org/10.48550/arXiv.2109.09901

A synthetic likelihood approach for intractable markov random fields

Wanchuang Zhu, Yanan Fan
Computational Statistics, Vol. 37, Issue 3, July 2022; https://doi.org/10.1007/s00180-022-01256-x

loopUI-0.1: indicators to support needs and practices in 3D geological modelling uncertainty quantification

Guillaume Pirot, Ranee Joshi, Jérémie Giraud, Mark Douglas Lindsay, and Mark Walter Jessell
Geosci. Model Dev., 15, 4689–4708, 2022; https://doi.org/10.5194/gmd-15-4689-2022

The Unexpected Oceanic Peak in Energy Input to the Atmosphere and Its Consequences for Monsoon Rainfall

Nandini Ramesh, William R. Boos
Geophysical Research Letter, Jun 2022; https://doi.org/10.1029/2022GL099283

Understanding Robust Overfitting of Adversarial Training and Beyond

Chaojian Yu, Bo Han, Li Shen, Jun Yu, Chen Gong, Mingming Gong, Tongliang Liu
Proceedings of the 39th International Conference on Machine Learning, 2022; https://doi.org/10.1029/2022GL099283

Coevolution of machine learning and process-based modelling to revolutionize Earth and environmental sciences: A perspective

Saman Razavi, David M. Hannah, Amin Elshorbagy, Sujay Kumar, Lucy Marshall, Dimitri P. Solomatine, Amin Dezfuli, Mojtaba Sadegh, James Famiglietti
Hydrological Processes, May 2022; https://doi.org/10.1002/hyp.14596

Blockworlds 0.1.0: a demonstration of anti-aliased geophysics for probabilistic inversions of implicit and kinematic geological models

Richard Scalzo, Mark Lindsay, Mark Jessell, Guillaume Pirot, Jeremie Giraud, Edward Cripps, and Sally Cripps
Geosci. Model Dev., 2022, 15, 3641–3662; https://doi.org/10.5194/gmd-15-3641-2022

Into the Noddyverse: a massive data store of 3D geological models for machine learning and inversion applications

Mark Jessell, Jiateng Guo, Yunqiang Li, Mark Lindsay, Richard Scalzo, Jérémie Giraud, Guillaume Pirot, Ed Cripps, and Vitaliy Ogarko
Earth Syst. Sci. Data, 14, 381–392, 2022; https://doi.org/10.5194/essd-14-381-2022

An Introduction to Quantum Computing for Statisticians and Data Scientists

Anna Lopatnikova, Minh-Ngoc Tran, Scott A. Sisson
Apr 2022; https://doi.org/10.48550/arXiv.2112.06587

Bayesian optimization with informative parametric models via sequential Monte Carlo

Rafael OliveiraRichard ScalzoRobert KohnSally CrippsKyle HardmanJohn CloseNasrin Taghavi and Charles Lemckert
Data-Centric EngineeringVolume 3, 2022, e5; https://doi.org/10.1017/dce.2022.5

Spatial and Temporal Global Patterns of Drought Propagation

Ignacio Fuentes, José Padarian and R. Willem Vervoort
Front. Environ. Sci., 01 March 2022; https://doi.org/10.3389/fenvs.2022.788248

A Comparative Study of Convolutional Neural Networks and Conventional Machine Learning Models for Lithological Mapping Using Remote Sensing Data

Shirmard H; Farahbakhsh E; Heidari E; Pour AB; Pradhan B; Müller D; Chandra R
Remote Sensing, 2022, vol. 14, pp. 819 – 819; http://dx.doi.org/10.3390/rs14040819

Progress in Developing Scale-Able Approaches to Field-Scale Water Accounting Based on Remote Sensing

Rutger Willem Vervoort, Ignacio Fuentes, Joost Brombacher, Jelle Degen, Pedro Chambel-Leitão and Flávio Santos
Sustainability, 2022, 14, 2732; https://doi.org/10.3390/su14052732

 

2021
Detecting Poisoning Nodes in Federated Learning by Ranking Gradients

Wanchuang Zhu, Benjamin ZH Zhao, Simon Luo, Ke Deng
Paper accepted in NeurIPS 2021 workshop

Distributed Bayesian optimisation framework for deep neuroevolution

Rohitash Chandra, Animesh Tiwari
Neurocomputing, Vol. 470, January 2022; https://doi.org/10.1016/j.neucom.2021.10.045

Bayesian LSTM with Stochastic Variational Inference for Estimating Model Uncertainty in Process-based Hydrological Models

Dayang Li, Lucy Marshall, Zhongmin Liang, Ashish Sharma, Yan Zhou
Water Resources Research, 09 September 2021; https://doi.org/10.1029/2021WR029772

‘You’ll Never Get Cultural Competence in Science’: An Australian Perspective on Integrating Cultural Competence into Science Teaching Via Cultural Accountability

Rebecca Cross, Rosanne Quinnell, Tina Bell, Paul Rhodes, Zsuzsanna Dancso, Thomas Hubble, Glenda Wardle, Melinda Lewis, Alice Motion, Dominic Murphy, Jaime Gongora
International Journal of Innovation in Science and Mathematics Education. Vol 29, No 3 (2021); http://dx.doi.org/10.30722/IJISME.29.03.005

Transboundary river basins: Scenarios of hydropower development and operation under extreme climate conditions

Kongmeng Ly, Graciela Metternicht, Lucy Marshall
Science of The Total Environment. 23 August 2021; https://doi.org/10.1016/j.scitotenv.2021.149828

Blockworlds 0.1.0: A demonstration of anti-aliased geophysics for probabilistic inversions of implicit and kinematic geological models

Richard Scalzo, Mark Lindsay, Mark Jessell, Guillaume Pirot, Jeremie Giraud, Edward Cripps, Sally Cripps
Geoscientific Model Development. Preprint, currently under review; https://doi.org/10.5194/gmd-2021-187

SMOTified-GAN for class imbalanced pattern classification problems

Anuraganand Sharma, Prabhat Kumar Singh, Rohitash Chandra
arXiv:2108.03235 [cs.LG]

Daily time series of river water levels derived from a seasonal linear model using multisource satellite products under uncertainty

Hung T. Pham, Lucy Marshall, Fiona Johnson
Journal of Hydrology. 5 August 2021; https://doi.org/10.1016/j.jhydrol.2021.126783

Phenotypic plasticity masks range- wide genetic differentiation for vegetative but not reproductive traits in a short- lived plant

Jesus Villellas, Johan Ehrlén, Elizabeth E. Crone, Glenda M. Wardle, et al.
Ecology Letters. 2021;00:1–16; https://doi.org/10.1111/ele.13858

Predicting the emplacement of Cordilleran porphyry copper systems using a spatio-temporal machine learning model

Julian Diaz-Rodriguez, R. Dietmar Müller, Rohitash Chandra
Ore Geology Reviews. Volume 137, October 2021, 104300; https://doi.org/10.1016/j.oregeorev.2021.104300

Partition-Mallows Model and Its Inference for Rank Aggregation

Wanchuang Zhu, Yingkai Jiang, Jun S. Liu, Ke Deng
Journal of the American Statistical Association. 28 May 2021; https://doi.org/10.1080/01621459.2021.1930547

Volume and uncertainty estimates of on-farm reservoirs using surface reflectance and LiDAR data

Ignacio Fuentes, Richard Scalzo, Willem Vervoort
Environmental Modelling and Software. Volume 143, 2021; https://doi.org/10.1016/j.envsoft.2021.105095

Quantifying input error in hydrologic modeling using the Bayesian error analysis with reordering (BEAR) approach

Xia Wu, Lucy Marshall, Ashish Sharma
Journal of Hydrology. Volume 598, July 2021; https://doi.org/10.1016/j.jhydrol.2021.126202

Dynamic models using score copula innovations

Landan Zhang, Michael K. Pitt, Robert Kohn
April 2021; https://doi.org/10.48550/arXiv.2104.00997

Structural, petrophysical and geological constraints in potential field inversion using the Tomofast-x v1.0 open-source code

Jeremie Giraud, Vitaliy Ogarko, Roland Martin, Mark Jessell, Mark Lindsay
Geoscientific Model Development. Discuss. [preprint], https://doi.org/10.5194/gmd-2021-14, in review, 2021.

Affordance Transfer Learning for Human-Object Interaction Detection

Zhi Hou, Baosheng Yu, Yu Qiao, Xiaojiang Peng, Dacheng Tao
Accepted to 2021 Conference on Computer Vision and Pattern Recognition

Precipitation reconstruction from climate-sensitive lithologies using Bayesian machine learning

Rohitash Chandra, Sally Cripps, Nathaniel Butterworth, R. Dietmar Muller
Environmental Modelling & Software. Volume 139, May 2021; https://doi.org/10.1016/j.envsoft.2021.105002

Generalization Bounds of Multitask Learning From Perspective of Vector-Valued Function Learning

Chao Zhang , Dacheng Tao, Tao Hu, Bingchen Liu
IEEE Transactions on Neural Networks and Learning Systems, Vol. 32, No.5, May 2021; DOI: 10.1109/TNNLS.2020.2995428

Revisiting Bayesian Autoencoders with MCMC

Rohitash Chandra, Mahir Jain, Manavendra Maharana, Pavel N. Krivitsky
arXiv:2104.05915 [cs.LG]

Generalization of level-set inversion to an arbitrary number of geological units in a regularized least-squares framework

Jérémie Giraud, Mark Lindsay, Mark Jessell
Geophysics. 13 April 2021; https://doi.org/10.1190/geo2020-0263.1

3D geological structure inversion from Noddy-generated magnetic data using deep learning methods

Jiateng Guo, Yunqiang Li, Mark Walter Jessell, Jeremie Giraud, Chaoling Li, Lixin Wu, Fengdan Li, Shanjun Liu,
Computers & Geosciences. Volume 149, April 2021; https://doi.org/10.1016/j.cageo.2021.104701.

Effect Estimates of COVID-19 Non-Pharmaceutical Interventions are Non-Robust and Highly Model-Dependent

Vincent Chin, John P.A. Ioannidis, Martin A. Tanner, Sally Cripps
Journal of Clinical Epidemiology. March 26, 2021; https://doi.org/10.1016/j.jclinepi.2021.03.014

Targeted Attention Attack on Deep Learning Models in Road Sign Recognition

Xinghao Yang , Weifeng Liu, Shengli Zhang, Wei Liu, Dacheng Tao
IEEE Internet of Things Journal, Vol. 8, No.6, March 15 2021; DOI: 10.1109/JIOT.2020.3034899

dh2loop 1.0: an open-source python library for automated processing and classification of geological logs

Ranee Joshi, Kavitha Madaiah, Mark Jessell, Mark Lindsay, Guillaume Pirot
Geoscientific Model Development. [preprint], https://doi.org/10.5194/gmd-2020-391, in review, 2021.

Deep learning via LSTM models for COVID-19 infection forecasting in India

Rohitash Chandra, Ayush Jain, Divyanshu Singh Chauhan
arXiv:2101.11881 [cs.LG]

Non-Volume Preserving Hamiltonian Monte Carlo and No-U-TurnSamplers

Sally Cripps, Hadi Afshar
To appear in the Proceedings of the 2021 International Conference on Artificial Intelligence and Statistics

Efficient Selection Between Hierarchical Cognitive Models: Cross-validation With Variational Bayes

Viet-Hung Dao, David Gunawan, Minh-Ngoc Tran, Robert Kohn, Guy E. Hawkins, Scott D. Brown
https://arxiv.org/abs/2102.06814

The Australian bushfire disaster: How to avoid repeating this catastrophe for biodiversity

Danielle Celermajer, Rosemary Lyster, Glenda M. Wardle, Rachel Walmsley, Ed Couzens
WIREs Climate Change. March 03, 2021; e704. https://doi.org/10.1002/wcc.704

Statistical finite elements for misspecified models

Connor Duffin, Edward Cripps, Thomas Stemler, Mark Girolami
Proceedings of the National Academy of Sciences. January 2021, 118 (2) e2015006118; DOI: 10.1073/pnas.2015006118

Automated geological map deconstruction for 3D model construction

Mark Jessell, Vitaliy Ogarko, Mark Lindsay, Ranee Joshi, Agnieszka Piechocka, Lachlan Grose, Miguel de la Varga, Laurent Ailleres, Guillaume Pirot
Geoscientific Model Development. [preprint], https://doi.org/10.5194/gmd-2020-400, in review, 2021.

Recursive Context Routing for Object Detection

Zhe Chen, Jing Zhang, Dacheng Tao
International Journal of Computer Vision (2021), 129:142–160; https://doi.org/10.1007/s11263-020-01370-7

Climate change and other trends in streamflow observations in Australian forested catchments since 1970

R. Willem Vervoort, Michaela M. Dolk, Floris F. van Ogtrop
Hydrological Processes. 2021; 35:e13999. https://doi.org/10.1002/hyp.13999

A Shape Transformation-based Dataset Augmentation Framework for Pedestrian Detection

Zhe Chen, Wanli Ouyang, Tongliang Liu, Dacheng Tao
International Journal of Computer Vision (2021), 129:1121–1138; https://doi.org/10.1007/s11263-020-01412-0

Genetic differentiation can be predicted from observational data for reproductive but not vegetative traits in a widespread short-lived plant

Jesus Villellas, Johan Ehrlén, Elizabeth Crone, et al.
Authorea. January 04, 2021. DOI: 10.22541/au.160975628.85388662/v1

2020
Mineral systems prospectivity modelling for gold and nickel in the Halls Creek Orogen, Western Australia

Fariba Kohanpour, Sandra Occhipinti, Mark Lindsay, Weronika Gorczyk, Fred Jourdan, Marc Poujol
Ore Geology Reviews. Volume 127, December 2020; https://doi.org/10.1016/j.oregeorev.2020.103809

The evolution from plate margin to intraplate mineral systems in the Capricorn Orogen, links to prospectivity

Sandra Occhipinti, Václav Metelka, Mark Lindsay, Alan Aitken, Franco Pirajno, Ian Tyler
Ore Geology Reviews. Volume 127, December 2020; https://doi.org/10.1016/j.oregeorev.2020.103811

Cooperative Inversion of Seismic and Gravity Data Using Weighted Structure-Based Constraints

Mahtab Rashidifard, Jeremie Giraud, Vitaliy Ogarko, Mark Jessell, Mark Lindsay
Proceedings of NSG2020 3rd Conference on Geophysics for Mineral Exploration and Mining. December 2020; https://doi.org/10.3997/2214-4609.202020042

Convex Optimization for Blind Source Separation on Statistical Manifolds

Simon Luo, Lamiae Azizi, Mahito Sugiyama
NeurIPS 2020 workshop on Differential Geometry meets Deep Learning. December 2020.

A Deep Architecture for Log-Linear Models

Simon Luo, Sally Cripps, Mahito Sugiyama
NeurIPS 2020 workshop on Differential Geometry meets Deep Learning. December 2020.

Building trust in SWAT model scenarios through a multi-institutional approach in Uruguay

Flora Mer, Walter Baethgen, R. Willem Vervoort
Socio-Environmental Systems Modelling. Volume 2, 2020; https://doi.org/10.18174/sesmo.2020a17892

Quantifying input uncertainty in the calibration of water quality models: reshuffling errors via the secant method

Xia Wu, Lucy Marshall, Ashish Sharma
Hydrology and Earth System Sciences. November 12, 2020; https://doi.org/10.5194/hess-2020-563

Improving the Combination of Satellite Soil Moisture Data Sets by Considering Error Cross Correlation: A Comparison Between Triple Collocation (TC) and Extended Double Instrumental Variable (EIVD) Alternatives

Seokhyeon Kim, Hung T. Pham, Yi Y. Liu, Lucy Marshall, Ashish Sharma
IEEE Transactions on Geoscience and Remote Sensing. November 02, 2020; doi: 10.1109/TGRS.2020.3032418.

Short-Term and Long-Term Context Aggregation Network for Video Inpainting

Ang Li, Shanshan Zhao, Xingjun Ma, Mingming Gong, Jianzhong Qi, Rui Zhang, Dacheng Tao, Ramamohanarao Kotagiri
European Conference on Computer Vision. Computer Vision – ECCV 2020 pp 728-743; https://doi.org/10.1007/978-3-030-58548-8_42

Towards plausible lithological classification from geophysical inversion: honouring geological principles in subsurface imaging

Jérémie Giraud, Mark Lindsay, Mark Jessell, Vitaliy Ogarko
Solid Earth, 11, 419–436, 2020; https://doi.org/10.5194/se-11-419-2020