Gal, Yarin

114 publications

ICLR 2025 AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents Maksym Andriushchenko, Alexandra Souly, Mateusz Dziemian, Derek Duenas, Maxwell Lin, Justin Wang, Dan Hendrycks, Andy Zou, J Zico Kolter, Matt Fredrikson, Yarin Gal, Xander Davies

ICLRW 2025 Attacking Multimodal OS Agents with Malicious Image Patches Lukas Aichberger, Alasdair Paren, Philip Torr, Yarin Gal, Adel Bibi

ICLRW 2025 Do Multilingual LLMs Think in English? Lisa Schut, Yarin Gal, Sebastian Farquhar

TMLR 2025 Explaining Explainability: Recommendations for Effective Use of Concept Activation Vectors Angus Nicolson, Lisa Schut, Alison Noble, Yarin Gal

NeurIPS 2025 Fundamental Limitations in Pointwise Defences of LLM Finetuning APIs Xander Davies, Eric Winsor, Alexandra Souly, Tomek Korbak, Robert Kirk, Christian Schroeder de Witt, Yarin Gal

NeurIPS 2025 MIP Against Agent: Malicious Image Patches Hijacking Multimodal OS Agents Lukas Aichberger, Alasdair Paren, Guohao Li, Philip Torr, Yarin Gal, Adel Bibi

NeurIPS 2025 Measuring What Matters: Construct Validity in Large Language Model Benchmarks Andrew M. Bean, Ryan Othniel Kearns, Angelika Romanou, Franziska Sofia Hafner, Harry Mayne, Jan Batzner, Negar Foroutan, Chris Schmitz, Karolina Korgul, Hunar Batra, Oishi Deb, Emma Beharry, Cornelius Emde, Thomas Foster, Anna Gausen, María Grandury, Simeng Han, Valentin Hofmann, Lujain Ibrahim, Hazel Kim, Hannah Rose Kirk, Fangru Lin, Gabrielle Kaili-May Liu, Lennart Luettgau, Jabez Magomere, Jonathan Rystrøm, Anna Sotnikova, Yushi Yang, Yilun Zhao, Adel Bibi, Antoine Bosselut, Ronald Clark, Arman Cohan, Jakob Nicolaus Foerster, Yarin Gal, Scott A. Hale, Inioluwa Deborah Raji, Christopher Summerfield, Philip Torr, Cozmin Ududec, Luc Rocher, Adam Mahdi

NeurIPS 2025 Memo: Training Memory-Efficient Embodied Agents with Reinforcement Learning Gunshi Gupta, Karmesh Yadav, Zsolt Kira, Yarin Gal, Rahaf Aljundi

TMLR 2025 Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities Zora Che, Stephen Casper, Robert Kirk, Anirudh Satheesh, Stewart Slocum, Lev E McKinney, Rohit Gandikota, Aidan Ewart, Domenic Rosati, Zichu Wu, Zikui Cai, Bilal Chughtai, Yarin Gal, Furong Huang, Dylan Hadfield-Menell

ICML 2025 Protriever: End-to-End Differentiable Protein Homology Search for Fitness Prediction Ruben Weitzman, Peter Mørch Groth, Lood Van Niekerk, Aoi Otani, Yarin Gal, Debora Susan Marks, Pascal Notin

ICLRW 2025 Protriever: End-to-End Differentiable Protein Homology Search for Fitness Prediction Ruben Weitzman, Peter Mørch Groth, Aoi Otani, Debora Susan Marks, Yarin Gal, Pascal Notin

NeurIPS 2025 SECODEPLT: A Unified Benchmark for Evaluating the Security Risks and Capabilities of Code GenAI Yuzhou Nie, Zhun Wang, Yu Yang, Ruizhe Jiang, Yuheng Tang, Xander Davies, Yarin Gal, Bo Li, Wenbo Guo, Dawn Song

ICLRW 2025 Sampling Protein Language Models for Functional Protein Design Jeremie Theddy Darmawan, Yarin Gal, Pascal Notin

NeurIPS 2025 Scaling up Active Testing to Large Language Models Gabrielle Berrada, Jannik Kossen, Freddie Bickford Smith, Muhammed Razzak, Yarin Gal, Tom Rainforth

NeurIPS 2025 Security Challenges in AI Agent Deployment: Insights from a Large Scale Public Competition Andy Zou, Maxwell Lin, Eliot Krzysztof Jones, Micha V. Nowak, Mateusz Dziemian, Nick Winter, Valent Nathanael, Ayla Croft, Xander Davies, Jai Patel, Robert Kirk, Yarin Gal, Dan Hendrycks, J Zico Kolter, Matt Fredrikson

NeurIPS 2025 Temporal-Difference Variational Continual Learning Luckeciano Carvalho Melo, Alessandro Abate, Yarin Gal

ICLRW 2025 Uncertainty-Aware Step-Wise Verification with Generative Reward Models Zihuiwen Ye, Luckeciano Carvalho Melo, Younesse Kaddar, Phil Blunsom, Sam Staton, Yarin Gal

ICML 2024 Challenges and Considerations in the Evaluation of Bayesian Causal Discovery Amir Mohammad Karimi Mamaghan, Panagiotis Tigas, Karl Henrik Johansson, Yarin Gal, Yashas Annadani, Stefan Bauer

NeurIPS 2024 Deep Bayesian Active Learning for Preference Modeling in Large Language Models Luckeciano C. Melo, Panagiotis Tigas, Alessandro Abate, Yarin Gal

NeurIPSW 2024 Efficient Experimentation for Estimation of Continuous and Discrete Conditional Treatment Effects Muhammed Razzak, Panagiotis Tigas, Andrew Jesson, Yarin Gal, Uri Shalit

NeurIPS 2024 Estimating the Hallucination Rate of Generative AI Andrew Jesson, Nicolas Beltran-Velez, Quentin Chu, Sweta Karlekar, Jannik Kossen, Yarin Gal, John P. Cunningham, David Blei

TMLR 2024 Fine-Tuning Can Cripple Your Foundation Model; Preserving Features May Be the Solution Jishnu Mukhoti, Yarin Gal, Philip Torr, Puneet K. Dokania

NeurIPSW 2024 Fine-Tuning Large Language Models to Appropriately Abstain with Semantic Entropy Benedict Aaron Tjandra, Muhammed Razzak, Jannik Kossen, Kunal Handa, Yarin Gal

ICLR 2024 How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions Lorenzo Pacchiardi, Alex James Chan, Sören Mindermann, Ilan Moscovitz, Alexa Yue Pan, Yarin Gal, Owain Evans, Jan M. Brauner

ICLR 2024 In-Context Learning Learns Label Relationships but Is Not Conventional Learning Jannik Kossen, Yarin Gal, Tom Rainforth

NeurIPS 2024 Kernel Language Entropy: Fine-Grained Uncertainty Quantification for LLMs from Semantic Similarities Alexander Nikitin, Jannik Kossen, Yarin Gal, Pekka Marttinen

ICML 2024 Position: Fundamental Limitations of LLM Censorship Necessitate New Approaches David Glukhov, Ilia Shumailov, Yarin Gal, Nicolas Papernot, Vardan Papyan

NeurIPS 2024 Pre-Trained Text-to-Image Diffusion Models Are Versatile Representation Learners for Control Gunshi Gupta, Karmesh Yadav, Yarin Gal, Zsolt Kira, Dhruv Batra, Cong Lu, Tim G. J. Rudner

ICLRW 2024 Pre-Trained Text-to-Image Diffusion Models Are Versatile Representation Learners for Control Gunshi Gupta, Karmesh Yadav, Yarin Gal, Dhruv Batra, Zsolt Kira, Cong Lu, Tim G. J. Rudner

ICML 2024 ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages Andrew Jesson, Chris Lu, Gunshi Gupta, Nicolas Beltran-Velez, Angelos Filos, Jakob Nicolaus Foerster, Yarin Gal

NeurIPSW 2024 Semantic Entropy Neurons: Encoding Semantic Uncertainty in the Latent Space of LLMs Jiatong Han, Jannik Kossen, Muhammed Razzak, Yarin Gal

ICMLW 2024 Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs Jiatong Han, Jannik Kossen, Muhammed Razzak, Lisa Schut, Shreshth A Malik, Yarin Gal

ICMLW 2024 Variational Inference Failures Under Model Symmetries: Permutation Invariant Posteriors for Bayesian Neural Networks Yoav Gelberg, Tycho F. A. van der Ouderaa, Mark van der Wilk, Yarin Gal

ICMLW 2023 BatchGFN: Generative Flow Networks for Batch Active Learning Shreshth A Malik, Salem Lahlou, Andrew Jesson, Moksh Jain, Nikolay Malkin, Tristan Deleu, Yoshua Bengio, Yarin Gal

ICMLW 2023 CLAM: Selective Clarification for Ambiguous Questions with Generative Language Models Lorenz Kuhn, Yarin Gal, Sebastian Farquhar

CLeaR 2023 Can Active Sampling Reduce Causal Confusion in Offline Reinforcement Learning? Gunshi Gupta, Tim G. J. Rudner, Rowan Thomas McAllister, Adrien Gaidon, Yarin Gal

CVPR 2023 Deep Deterministic Uncertainty: A New Simple Baseline Jishnu Mukhoti, Andreas Kirsch, Joost van Amersfoort, Philip H.S. Torr, Yarin Gal

ICML 2023 Differentiable Multi-Target Causal Bayesian Experimental Design Panagiotis Tigas, Yashas Annadani, Desi R. Ivanova, Andrew Jesson, Yarin Gal, Adam Foster, Stefan Bauer

ICLRW 2023 Differentiable Multi-Target Causal Bayesian Experimental Design Panagiotis Tigas, Yashas Annadani, Desi R. Ivanova, Andrew Jesson, Yarin Gal, Adam Foster, Stefan Bauer

ICML 2023 DiscoBAX: Discovery of Optimal Intervention Sets in Genomic Experiment Design Clare Lyle, Arash Mehrjou, Pascal Notin, Andrew Jesson, Stefan Bauer, Yarin Gal, Patrick Schwab

ICLRW 2023 DyNeMoC: A Semi-Supervised Architecture for Classifying Time Series Brain Data Abu Mohammad Shabbir Khan, Chetan Gohil, Pascal Notin, Joost van Amersfoort, Mark Woolrich, Yarin Gal

AISTATS 2023 Prediction-Oriented Bayesian Active Learning Freddie Bickford Smith, Andreas Kirsch, Sebastian Farquhar, Yarin Gal, Adam Foster, Tom Rainforth

NeurIPS 2023 ProteinGym: Large-Scale Benchmarks for Protein Fitness Prediction and Design Pascal Notin, Aaron Kollasch, Daniel Ritter, Lood van Niekerk, Steffanie Paul, Han Spinner, Nathan Rollins, Ada Shaw, Rose Orenbuch, Ruben Weitzman, Jonathan Frazer, Mafalda Dias, Dinko Franceschi, Yarin Gal, Debora Marks

NeurIPS 2023 ProteinNPT: Improving Protein Property Prediction and Design with Non-Parametric Transformers Pascal Notin, Ruben Weitzman, Debora Marks, Yarin Gal

NeurIPSW 2023 Sampling Protein Language Models for Functional Protein Design Jeremie Theddy Darmawan, Yarin Gal, Pascal Notin

ICLR 2023 Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation Lorenz Kuhn, Yarin Gal, Sebastian Farquhar

TMLR 2023 Stochastic Batch Acquisition: A Simple Baseline for Deep Active Learning Andreas Kirsch, Sebastian Farquhar, Parmida Atighehchian, Andrew Jesson, Frédéric Branchaud-Charron, Yarin Gal

TMLR 2022 A Note on "Assessing Generalization of SGD via Disagreement" Andreas Kirsch, Yarin Gal

NeurIPS 2022 Active Surrogate Estimators: An Active Learning Approach to Label-Efficient Model Evaluation Jannik Kossen, Sebastian Farquhar, Yarin Gal, Thomas Rainforth

NeurIPSW 2022 Can Active Sampling Reduce Causal Confusion in Offline Reinforcement Learning? Gunshi Gupta, Tim G. J. Rudner, Rowan Thomas McAllister, Adrien Gaidon, Yarin Gal

ICML 2022 Continual Learning via Sequential Function-Space Variational Inference Tim G. J. Rudner, Freddie Bickford Smith, Qixuan Feng, Yee Whye Teh, Yarin Gal

ICLR 2022 GeneDisco: A Benchmark for Experimental Design in Drug Discovery Arash Mehrjou, Ashkan Soleymani, Andrew Jesson, Pascal Notin, Yarin Gal, Stefan Bauer, Patrick Schwab

JMLR 2022 Interlocking Backpropagation: Improving Depthwise Model-Parallelism Aidan N. Gomez, Oscar Key, Kuba Perlin, Stephen Gou, Nick Frosst, Jeff Dean, Yarin Gal

NeurIPS 2022 Interventions, Where and How? Experimental Design for Causal Models at Scale Panagiotis Tigas, Yashas Annadani, Andrew Jesson, Bernhard Schölkopf, Yarin Gal, Stefan Bauer

ICLR 2022 KL Guided Domain Adaptation A. Tuan Nguyen, Toan Tran, Yarin Gal, Philip Torr, Atilim Gunes Baydin

ICML 2022 Learning Dynamics and Generalization in Deep Reinforcement Learning Clare Lyle, Mark Rowland, Will Dabney, Marta Kwiatkowska, Yarin Gal

ICMLW 2022 Plex: Towards Reliability Using Pretrained Large Model Extensions Dustin Tran, Jeremiah Zhe Liu, Michael W Dusenberry, Du Phan, Mark Collier, Jie Ren, Kehang Han, Zi Wang, Zelda E Mariet, Huiyi Hu, Neil Band, Tim G. J. Rudner, Karan Singhal, Zachary Nado, Joost van Amersfoort, Andreas Kirsch, Rodolphe Jenatton, Nithum Thain, Honglin Yuan, E. Kelly Buchanan, Kevin Patrick Murphy, D. Sculley, Yarin Gal, Zoubin Ghahramani, Jasper Snoek, Balaji Lakshminarayanan

ICML 2022 Prioritized Training on Points That Are Learnable, Worth Learning, and Not yet Learnt Sören Mindermann, Jan M Brauner, Muhammed T Razzak, Mrinank Sharma, Andreas Kirsch, Winnie Xu, Benedikt Höltgen, Aidan N Gomez, Adrien Morisot, Sebastian Farquhar, Yarin Gal

ICLR 2022 Prospect Pruning: Finding Trainable Weights at Initialization Using Meta-Gradients Milad Alizadeh, Shyam A. Tailor, Luisa M Zintgraf, Joost van Amersfoort, Sebastian Farquhar, Nicholas Donald Lane, Yarin Gal

NeurIPS 2022 Scalable Sensitivity and Uncertainty Analyses for Causal-Effect Estimates of Continuous-Valued Interventions Andrew Jesson, Alyson Douglas, Peter Manshausen, Maëlys Solal, Nicolai Meinshausen, Philip Stier, Yarin Gal, Uri Shalit

NeurIPSW 2022 Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation Lorenz Kuhn, Yarin Gal, Sebastian Farquhar

NeurIPS 2022 Tractable Function-Space Variational Inference in Bayesian Neural Networks Tim G. J. Rudner, Zonghao Chen, Yee Whye Teh, Yarin Gal

NeurIPSW 2022 TranceptEVE: Combining Family-Specific and Family-Agnostic Models of Protein Sequences for Improved Fitness Prediction Pascal Notin, Lood Van Niekerk, Aaron W Kollasch, Daniel Ritter, Yarin Gal, Debora Susan Marks

ICML 2022 Tranception: Protein Fitness Prediction with Autoregressive Transformers and Inference-Time Retrieval Pascal Notin, Mafalda Dias, Jonathan Frazer, Javier Marchena-Hurtado, Aidan N Gomez, Debora Marks, Yarin Gal

TMLR 2022 Unifying Approaches in Active Learning and Active Sampling via Fisher Information and Information-Theoretic Quantities Andreas Kirsch, Yarin Gal

NeurIPSW 2022 What 'Out-of-Distribution' Is and Is Not Sebastian Farquhar, Yarin Gal

AISTATS 2021 Generating Interpretable Counterfactual Explanations by Implicit Minimisation of Epistemic and Aleatoric Uncertainties Lisa Schut, Oscar Key, Rory Mc Grath, Luca Costabello, Bogdan Sacaleanu, Medb Corcoran, Yarin Gal

ICML 2021 Active Testing: Sample-Efficient Model Evaluation Jannik Kossen, Sebastian Farquhar, Yarin Gal, Tom Rainforth

NeurIPSW 2021 Benchmarking Bayesian Deep Learning on Diabetic Retinopathy Detection Tasks Neil Band, Tim G. J. Rudner, Qixuan Feng, Angelos Filos, Zachary Nado, Michael W Dusenberry, Ghassen Jerfel, Dustin Tran, Yarin Gal

NeurIPS 2021 Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data Andrew Jesson, Panagiotis Tigas, Joost van Amersfoort, Andreas Kirsch, Uri Shalit, Yarin Gal

NeurIPSW 2021 DARTS Without a Validation Set: Optimizing the Marginal Likelihood Miroslav Fil, Binxin Ru, Clare Lyle, Yarin Gal

NeurIPSW 2021 DeDUCE: Generating Counterfactual Explanations at Scale Benedikt Höltgen, Lisa Schut, Jan M. Brauner, Yarin Gal

NeurIPS 2021 Domain Invariant Representation Learning with Domain Density Transformations A. Tuan Nguyen, Toan Tran, Yarin Gal, Atilim Gunes Baydin

NeurIPS 2021 Improving Black-Box Optimization in VAE Latent Space Using Decoder Uncertainty Pascal Notin, José Miguel Hernández-Lobato, Yarin Gal

ICLR 2021 Learning Invariant Representations for Reinforcement Learning Without Reconstruction Amy Zhang, Rowan Thomas McAllister, Roberto Calandra, Yarin Gal, Sergey Levine

NeurIPS 2021 On Pathologies in KL-Regularized Reinforcement Learning from Expert Demonstrations Tim G. J. Rudner, Cong Lu, Michael A Osborne, Yarin Gal, Yee W. Teh

ICML 2021 On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes Tim G. J. Rudner, Oscar Key, Yarin Gal, Tom Rainforth

ICLR 2021 On Statistical Bias in Active Learning: How and When to Fix It Sebastian Farquhar, Yarin Gal, Tom Rainforth

NeurIPS 2021 Outcome-Driven Reinforcement Learning via Variational Inference Tim G. J. Rudner, Vitchyr Pong, Rowan McAllister, Yarin Gal, Sergey Levine

ICML 2021 PsiPhi-Learning: Reinforcement Learning with Demonstrations Using Successor Features and Inverse Temporal Difference Learning Angelos Filos, Clare Lyle, Yarin Gal, Sergey Levine, Natasha Jaques, Gregory Farquhar

ICML 2021 Quantifying Ignorance in Individual-Level Causal-Effect Estimates Under Hidden Confounding Andrew Jesson, Sören Mindermann, Yarin Gal, Uri Shalit

NeurIPS 2021 Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning Jannik Kossen, Neil Band, Clare Lyle, Aidan N Gomez, Thomas Rainforth, Yarin Gal

NeurIPS 2021 Speedy Performance Estimation for Neural Architecture Search Robin Ru, Clare Lyle, Lisa Schut, Miroslav Fil, Mark van der Wilk, Yarin Gal

JMLR 2021 VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning Luisa Zintgraf, Sebastian Schulze, Cong Lu, Leo Feng, Maximilian Igl, Kyriacos Shiarlis, Yarin Gal, Katja Hofmann, Shimon Whiteson

NeurIPS 2020 A Bayesian Perspective on Training Speed and Model Selection Clare Lyle, Lisa Schut, Robin Ru, Yarin Gal, Mark van der Wilk

ICLR 2020 BayesOpt Adversarial Attack Binxin Ru, Adam Cobb, Arno Blaas, Yarin Gal

ICML 2020 Can Autonomous Vehicles Identify, Recover from, and Adapt to Distribution Shifts? Angelos Filos, Panagiotis Tigkas, Rowan Mcallister, Nicholas Rhinehart, Sergey Levine, Yarin Gal

NeurIPS 2020 How Robust Are the Estimated Effects of Nonpharmaceutical Interventions Against COVID-19? Mrinank Sharma, Sören Mindermann, Jan Brauner, Gavin Leech, Anna Stephenson, Tomáš Gavenčiak, Jan Kulveit, Yee Whye Teh, Leonid Chindelevitch, Yarin Gal

NeurIPS 2020 Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models Andrew Jesson, Sören Mindermann, Uri Shalit, Yarin Gal

ICML 2020 Inter-Domain Deep Gaussian Processes Tim G. J. Rudner, Dino Sejdinovic, Yarin Gal

ICML 2020 Invariant Causal Prediction for Block MDPs Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup

NeurIPS 2020 Liberty or Depth: Deep Bayesian Neural Nets Do Not Need Complex Weight Posterior Approximations Sebastian Farquhar, Lewis Smith, Yarin Gal

AISTATS 2020 Radial Bayesian Neural Networks: Beyond Discrete Support in Large-Scale Bayesian Deep Learning Sebastian Farquhar, Michael A. Osborne, Yarin Gal

ICML 2020 Uncertainty Estimation Using a Single Deep Deterministic Neural Network Joost Van Amersfoort, Lewis Smith, Yee Whye Teh, Yarin Gal

ICLR 2020 VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning Luisa Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson

ICLR 2019 An Empirical Study of Binary Neural Networks' Optimisation Milad Alizadeh, Javier Fernández-Marqués, Nicholas D. Lane, Yarin Gal

NeurIPS 2019 BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning Andreas Kirsch, Joost van Amersfoort, Yarin Gal

NeurIPS 2018 BRUNO: A Deep Recurrent Model for Exchangeable Data Iryna Korshunova, Jonas Degrave, Ferenc Huszar, Yarin Gal, Arthur Gretton, Joni Dambre

ICML 2018 Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Khan, Didrik Nielsen, Voot Tangkaratt, Wu Lin, Yarin Gal, Akash Srivastava

UAI 2018 Understanding Measures of Uncertainty for Adversarial Example Detection Lewis Smith, Yarin Gal

NeurIPS 2017 Concrete Dropout Yarin Gal, Jiri Hron, Alex Kendall

IJCAI 2017 Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning Rowan McAllister, Yarin Gal, Alex Kendall, Mark van der Wilk, Amar Shah, Roberto Cipolla, Adrian Weller

ICML 2017 Deep Bayesian Active Learning with Image Data Yarin Gal, Riashat Islam, Zoubin Ghahramani

ICML 2017 Dropout Inference in Bayesian Neural Networks with Alpha-Divergences Yingzhen Li, Yarin Gal

NeurIPS 2017 Real Time Image Saliency for Black Box Classifiers Piotr Dabkowski, Yarin Gal

NeurIPS 2017 What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall, Yarin Gal

NeurIPS 2016 A Theoretically Grounded Application of Dropout in Recurrent Neural Networks Yarin Gal, Zoubin Ghahramani

ICML 2016 Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Yarin Gal, Zoubin Ghahramani

ICML 2015 Improving the Gaussian Process Sparse Spectrum Approximation by Representing Uncertainty in Frequency Inputs Yarin Gal, Richard Turner

ICML 2015 Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data Yarin Gal, Yutian Chen, Zoubin Ghahramani

NeurIPS 2014 Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models Yarin Gal, Mark van der Wilk, Carl Edward Rasmussen

ICML 2014 Pitfalls in the Use of Parallel Inference for the Dirichlet Process Yarin Gal, Zoubin Ghahramani