Amir Dezfouli
14 papers · 2015–2026 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+3 more ↓ Show less ↑
π£ Hot Topic Early Bird π Conference Polyglot Β· Silver π Academic Marathon Β· Half π Interdisciplinary Bridge Β· Silver πΊοΈ Taxonomy Completionist (33)
π
Century Club Β· Bronze
π
Renaissance Researcher
(7)
ποΈ
Keyword Collector
(77)
Top co-authors
Research topics
Machine Learning
(12)
Core Methods
(7)
Artificial Intelligence
(6)
Optimization & Theory
(6)
Deep Learning
(5)
Architectures
(4)
Bayesian & Probabilistic Β· Machine Learning
(4)
Core AI
(4)
Learning Types
(4)
Healthcare & Medicine
(2)
Knowledge & Reasoning
(2)
Bayesian & Probabilistic Β· Artificial Intelligence
(2)
Interdisciplinary
(1)
Mathematics & Optimization
(1)
Natural Language Processing
(1)
Keywords
gaussian process
(4)
variational inference
(4)
recurrent neural network
(3)
interactive theorem proving
(2)
deep reinforcement learning
(2)
latent space
(2)
brain-computer interface
(1)
black-box optimization
(1)
transformer architecture
(1)
feature selection
(1)
spatio-temporal modeling
(1)
automated reasoning
(1)
natural language processing
(1)
markov decision process
(1)
probabilistic modeling
(1)
brain imaging
(1)
network inference
(1)
structured prediction
(1)
point process
(1)
distribution matching
(1)
Papers
Leveraging Sparse Observations to Predict Species Abundance Across Space and Time
AAAI 2026
BAIT: Benchmarking (Embedding) Architectures for Interactive Theorem-Proving
AAAI 2024
Mixed-Variable Black-Box Optimisation Using Value Proposal Trees
AAAI 2023
The Contextual Lasso: Sparse Linear Models via Deep Neural Networks
NeurIPS 2023
Transformed Distribution Matching for Missing Value Imputation
ICML 2023
Neural Network Poisson Models for Behavioural and Neural Spike Train Data
ICML 2022
Optimizing Sequential Experimental Design with Deep Reinforcement Learning
ICML 2022
TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement Learning
NeurIPS 2021
Disentangled behavioural representations
NeurIPS 2019
Generic Inference in Latent Gaussian Process Models
JMLR 2019
Integrated accounts of behavioral and neuroimaging data using flexible recurrent neural network models
NeurIPS 2018
Variational Network Inference: Strong and Stable with Concrete Support
ICML 2018
Gray-box Inference for Structured Gaussian Process Models
AISTATS 2017
Scalable Inference for Gaussian Process Models with Black-Box Likelihoods
NeurIPS 2015