Amir Dezfouli

37 papers A* 11A 1Journal 22Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
Free Lunch for Pass@k? Low Cost Diverse Sampling for Diffusion Language Models.
CoRR
Sean Lamont, Christian Walder, Paul Montague, Amir Dezfouli, Michael Norrish
2026 A* conf
Leveraging Sparse Observations to Predict Species Abundance Across Space and Time.
AAAI
Md Zahidul Islam, Cameron S. Fletcher, Ke Sun, Amir Dezfouli, Iadine Chades
2024 J jnl
3D-Prover: Diversity Driven Theorem Proving With Determinantal Point Processes.
CoRR
Sean Lamont, Christian Walder, Amir Dezfouli, Paul Montague, Michael Norrish
2024 — conf
Approximate Nearest Neighbour Search on Dynamic Datasets: An Investigation.
AI (2)
Ben Harwood, Amir Dezfouli, Iadine Chades, Conrad Sanderson
2024 J jnl
Approximate Nearest Neighbour Search on Dynamic Datasets: An Investigation.
CoRR
Ben Harwood, Amir Dezfouli, Iadine Chades, Conrad Sanderson
2024 A* conf
BAIT: Benchmarking (Embedding) Architectures for Interactive Theorem-Proving.
AAAI
Sean Lamont, Michael Norrish, Amir Dezfouli, Christian Walder, Paul Montague
2024 J jnl
BAIT: Benchmarking (Embedding) Architectures for Interactive Theorem-Proving.
CoRR
Sean Lamont, Michael Norrish, Amir Dezfouli, Christian Walder, Paul Montague
2023 J jnl
Cross-Entropy Estimators for Sequential Experiment Design with Reinforcement Learning.
CoRR
Tom Blau, Edwin V. Bonilla, Iadine Chades, Amir Dezfouli
2023 A* conf
Mixed-Variable Black-Box Optimisation Using Value Proposal Trees.
AAAI
Yan Zuo, Vu Nguyen, Amir Dezfouli, David Alexander, Benjamin Ward Muir, Iadine Chades
2023 A* conf
The Contextual Lasso: Sparse Linear Models via Deep Neural Networks.
NeurIPS
Ryan Thompson, Amir Dezfouli, Robert Kohn
2023 J jnl
The Contextual Lasso: Sparse Linear Models via Deep Neural Networks.
CoRR
Ryan Thompson, Amir Dezfouli, Robert Kohn
2023 A* conf
Transformed Distribution Matching for Missing Value Imputation.
ICML
He Zhao, Ke Sun, Amir Dezfouli, Edwin V. Bonilla
2023 J jnl
Transformed Distribution Matching for Missing Value Imputation.
CoRR
He Zhao, Ke Sun, Amir Dezfouli, Edwin V. Bonilla
2022 J jnl
Bayesian Optimisation for Mixed-Variable Inputs using Value Proposals.
CoRR
Yan Zuo, Amir Dezfouli, Iadine Chades, David Alexander, Benjamin Ward Muir
2022 J jnl
EAPS: Edge-Assisted Predictive Sleep Scheduling for 802.11 IoT Stations.
IEEE Syst. J.
Jaykumar Sheth, Cyrus Miremadi, Amir Dezfouli, Behnam Dezfouli
2022 A* conf
Neural Network Poisson Models for Behavioural and Neural Spike Train Data.
ICML
Moein Khajehnejad, Forough Habibollahi, Richard Nock, Ehsan Arabzadeh, Peter Dayan, Amir Dezfouli
2022 A* conf
Optimizing Sequential Experimental Design with Deep Reinforcement Learning.
ICML
Tom Blau, Edwin V. Bonilla, Iadine Chades, Amir Dezfouli
2022 J jnl
Optimizing Sequential Experimental Design with Deep Reinforcement Learning.
CoRR
Tom Blau, Edwin V. Bonilla, Amir Dezfouli, Iadine Chades
2021 A* conf
TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement Learning.
NeurIPS
Minchao Wu, Michael Norrish, Christian Walder, Amir Dezfouli
2021 J jnl
TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement Learning.
CoRR
Minchao Wu, Michael Norrish, Christian Walder, Amir Dezfouli
2020 J jnl
EAPS: Edge-Assisted Predictive Sleep Scheduling for 802.11 IoT Stations.
CoRR
Jaykumar Sheth, Cyrus Miremadi, Amir Dezfouli, Behnam Dezfouli
2019 A* conf
Disentangled behavioural representations.
NeurIPS
Amir Dezfouli, Hassan Ashtiani, Omar Ghattas, Richard Nock, Peter Dayan, Cheng Soon Ong
2019 J jnl
Generic Inference in Latent Gaussian Process Models.
J. Mach. Learn. Res.
Edwin V. Bonilla, Karl Krauth, Amir Dezfouli
2019 J jnl
Hierarchical Bayesian inference for concurrent model fitting and comparison for group studies.
PLoS Comput. Biol.
Payam Piray, Amir Dezfouli, Tom Heskes, Michael J. Frank, Nathaniel D. Daw
2019 J jnl
Learning the structure of the world: The adaptive nature of state-space and action representations in multi-stage decision-making.
PLoS Comput. Biol.
Amir Dezfouli, Bernard W. Balleine
2019 J jnl
Models that learn how humans learn: The case of decision-making and its disorders.
PLoS Comput. Biol.
Amir Dezfouli, Kristi Griffiths, Fabio Ramos, Peter Dayan, Bernard W. Balleine
2019 J jnl
Optimizing the depth and the direction of prospective planning using information values.
PLoS Comput. Biol.
Can Eren Sezener, Amir Dezfouli, Mohammad Mehdi Keramati
2018 A* conf
Integrated accounts of behavioral and neuroimaging data using flexible recurrent neural network models.
NeurIPS
Amir Dezfouli, Richard W. Morris, Fabio T. Ramos, Peter Dayan, Bernard W. Balleine
2018 A* conf
Variational Network Inference: Strong and Stable with Concrete Support.
ICML
Amir Dezfouli, Edwin V. Bonilla, Richard Nock
2017 A conf
Gray-box Inference for Structured Gaussian Process Models.
AISTATS
Pietro Galliani, Amir Dezfouli, Edwin V. Bonilla, Novi Quadrianto
2017 J jnl
Semi-parametric Network Structure Discovery Models.
CoRR
Amir Dezfouli, Edwin V. Bonilla, Richard Nock
2015 — —
Hierarchical models of goal-directed and automatic actions.
Amir Dezfouli
2015 — conf
Scalable Inference for Gaussian Process Models with Black-Box Likelihoods.
NIPS
Amir Dezfouli, Edwin V. Bonilla
2013 J jnl
Actions, Action Sequences and Habits: Evidence That Goal-Directed and Habitual Action Control Are Hierarchically Organized.
PLoS Comput. Biol.
Amir Dezfouli, Bernard W. Balleine
2011 J jnl
Speed/Accuracy Trade-Off between the Habitual and the Goal-Directed Processes.
PLoS Comput. Biol.
Mohammad Mehdi Keramati, Amir Dezfouli, Payam Piray
2010 J jnl
Individual Differences in Nucleus Accumbens Dopamine Receptors Predict Development of Addiction-Like Behavior: A Computational Approach.
Neural Comput.
Payam Piray, Mohammad Mahdi Keramati, Amir Dezfouli, Caro Lucas, Azarakhsh Mokri
2009 J jnl
A Neurocomputational Model for Cocaine Addiction.
Neural Comput.
Amir Dezfouli, Payam Piray, Mohammad Mahdi Keramati, Hamed Ekhtiari, Caro Lucas, Azarakhsh Mokri