Dezfouli, Amir

15 publications

NeurIPS 2025 3D-Prover: Diversity Driven Theorem Proving with Determinantal Point Processes Sean Lamont, Christian Walder, Amir Dezfouli, Paul Montague, Michael Norrish

AAAI 2024 BAIT: Benchmarking (Embedding) Architectures for Interactive Theorem-Proving Sean Lamont, Michael Norrish, Amir Dezfouli, Christian Walder, Paul Montague

NeurIPSW 2023 Cross-Entropy Estimators for Sequential Experiment Design with Reinforcement Learning Tom Blau, Iadine Chades, Amir Dezfouli, Daniel M Steinberg, Edwin V. Bonilla

AAAI 2023 Mixed-Variable Black-Box Optimisation Using Value Proposal Trees Yan Zuo, Vu Nguyen, Amir Dezfouli, David Alexander, Benjamin Ward Muir, Iadine Chades

NeurIPS 2023 The Contextual Lasso: Sparse Linear Models via Deep Neural Networks Ryan Thompson, Amir Dezfouli, Robert Kohn

ICML 2023 Transformed Distribution Matching for Missing Value Imputation He Zhao, Ke Sun, Amir Dezfouli, Edwin V. Bonilla

ICML 2022 Neural Network Poisson Models for Behavioural and Neural Spike Train Data Moein Khajehnejad, Forough Habibollahi, Richard Nock, Ehsan Arabzadeh, Peter Dayan, Amir Dezfouli

ICML 2022 Optimizing Sequential Experimental Design with Deep Reinforcement Learning Tom Blau, Edwin V. Bonilla, Iadine Chades, Amir Dezfouli

NeurIPS 2021 TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement Learning Minchao Wu, Michael Norrish, Christian Walder, Amir Dezfouli

NeurIPS 2019 Disentangled Behavioural Representations Amir Dezfouli, Hassan Ashtiani, Omar Ghattas, Richard Nock, Peter Dayan, Cheng Soon Ong

JMLR 2019 Generic Inference in Latent Gaussian Process Models Edwin V. Bonilla, Karl Krauth, Amir Dezfouli

NeurIPS 2018 Integrated Accounts of Behavioral and Neuroimaging Data Using Flexible Recurrent Neural Network Models Amir Dezfouli, Richard Morris, Fabio T Ramos, Peter Dayan, Bernard Balleine

ICML 2018 Variational Network Inference: Strong and Stable with Concrete Support Amir Dezfouli, Edwin Bonilla, Richard Nock

AISTATS 2017 Gray-Box Inference for Structured Gaussian Process Models Pietro Galliani, Amir Dezfouli, Edwin V. Bonilla, Novi Quadrianto

NeurIPS 2015 Scalable Inference for Gaussian Process Models with Black-Box Likelihoods Amir Dezfouli, Edwin V. Bonilla