Amir Dezfouli

According to our database, Amir Dezfouli authored at least 26 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

BAIT: Benchmarking (Embedding) Architectures for Interactive Theorem-Proving.

Sean Lamont, Michael Norrish, Amir Dezfouli, Christian Walder, Paul Montague

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Cross-Entropy Estimators for Sequential Experiment Design with Reinforcement Learning.

Tom Blau, Edwin Bonilla, Iadine Chades, Amir Dezfouli

CoRR, 2023

The Contextual Lasso: Sparse Linear Models via Deep Neural Networks.

Ryan Thompson, Amir Dezfouli, Robert Kohn

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Transformed Distribution Matching for Missing Value Imputation.

He Zhao, Ke Sun, Amir Dezfouli, Edwin V. Bonilla

Proceedings of the International Conference on Machine Learning, 2023

Mixed-Variable Black-Box Optimisation Using Value Proposal Trees.

Yan Zuo, Vu Nguyen, Amir Dezfouli, David Alexander, Benjamin Ward Muir, Iadine Chades

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

EAPS: Edge-Assisted Predictive Sleep Scheduling for 802.11 IoT Stations.

Jaykumar Sheth, Cyrus Miremadi, Amir Dezfouli, Behnam Dezfouli

IEEE Syst. J., 2022

Bayesian Optimisation for Mixed-Variable Inputs using Value Proposals.

Yan Zuo, Amir Dezfouli, Iadine Chades, David Alexander, Benjamin Ward Muir

CoRR, 2022

Neural Network Poisson Models for Behavioural and Neural Spike Train Data.

Moein Khajehnejad, Forough Habibollahi, Richard Nock, Ehsan Arabzadeh, Peter Dayan, Amir Dezfouli

Proceedings of the International Conference on Machine Learning, 2022

Optimizing Sequential Experimental Design with Deep Reinforcement Learning.

Tom Blau, Edwin V. Bonilla, Iadine Chades, Amir Dezfouli

Proceedings of the International Conference on Machine Learning, 2022

2021

TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement Learning.

Minchao Wu, Michael Norrish, Christian Walder, Amir Dezfouli

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2019

Optimizing the depth and the direction of prospective planning using information values.

Can Eren Sezener, Amir Dezfouli, Mohammad Mehdi Keramati

PLoS Comput. Biol., 2019

Hierarchical Bayesian inference for concurrent model fitting and comparison for group studies.

Payam Piray, Amir Dezfouli, Tom Heskes, Michael J. Frank, Nathaniel D. Daw

PLoS Comput. Biol., 2019

Models that learn how humans learn: The case of decision-making and its disorders.

Amir Dezfouli, Kristi Griffiths, Fabio Ramos, Peter Dayan, Bernard W. Balleine

PLoS Comput. Biol., 2019

Learning the structure of the world: The adaptive nature of state-space and action representations in multi-stage decision-making.

Amir Dezfouli, Bernard W. Balleine

PLoS Comput. Biol., 2019

Generic Inference in Latent Gaussian Process Models.

Edwin V. Bonilla, Karl Krauth, Amir Dezfouli

J. Mach. Learn. Res., 2019

Disentangled behavioural representations.

Amir Dezfouli, Hassan Ashtiani, Omar Ghattas, Richard Nock, Peter Dayan, Cheng Soon Ong

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Integrated accounts of behavioral and neuroimaging data using flexible recurrent neural network models.

Amir Dezfouli, Richard W. Morris, Fabio T. Ramos, Peter Dayan, Bernard W. Balleine

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Variational Network Inference: Strong and Stable with Concrete Support.

Amir Dezfouli, Edwin V. Bonilla, Richard Nock

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Semi-parametric Network Structure Discovery Models.

Amir Dezfouli, Edwin V. Bonilla, Richard Nock

CoRR, 2017

Gray-box Inference for Structured Gaussian Process Models.

Pietro Galliani, Amir Dezfouli, Edwin V. Bonilla, Novi Quadrianto

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2015

Hierarchical models of goal-directed and automatic actions.

Amir Dezfouli

PhD thesis, 2015

Scalable Inference for Gaussian Process Models with Black-Box Likelihoods.

Amir Dezfouli, Edwin V. Bonilla

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2013

Actions, Action Sequences and Habits: Evidence That Goal-Directed and Habitual Action Control Are Hierarchically Organized.

Amir Dezfouli, Bernard W. Balleine

PLoS Comput. Biol., 2013

2011

Speed/Accuracy Trade-Off between the Habitual and the Goal-Directed Processes.

Mohammad Mehdi Keramati, Amir Dezfouli, Payam Piray

PLoS Comput. Biol., 2011

2010

Individual Differences in Nucleus Accumbens Dopamine Receptors Predict Development of Addiction-Like Behavior: A Computational Approach.

Payam Piray, Mohammad Mahdi Keramati, Amir Dezfouli, Caro Lucas, Azarakhsh Mokri

Neural Comput., 2010

2009

A Neurocomputational Model for Cocaine Addiction.

Amir Dezfouli, Payam Piray, Mohammad Mahdi Keramati, Hamed Ekhtiari, Caro Lucas, Azarakhsh Mokri

Neural Comput., 2009