Tuan Anh Le
19 papers · 2015–2024 · 8 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (33) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Keyword Champion
(3)
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Grand Slam
π§¬
Topic Evolution
π
Renaissance Researcher
(5)
π₯
Unstoppable Β· Bronze
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Conference Pioneer
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Century Club Β· Bronze
ποΈ
Keyword Collector
(91)
Top co-authors
Research topics
Machine Learning
(13)
Deep Learning
(11)
Artificial Intelligence
(10)
Models
(10)
Optimization & Theory
(8)
Bayesian & Probabilistic Β· Machine Learning
(6)
Bayesian & Probabilistic Β· Artificial Intelligence
(5)
Core AI
(4)
Learning Paradigms
(3)
Learning Types Β· Deep Learning
(3)
Learning Types Β· Machine Learning
(3)
Computer Vision
(2)
Reinforcement Learning
(2)
Analysis
(2)
Natural Language Processing
(1)
Keywords
variational inference
(7)
generative model
(6)
amortized inference
(5)
evidence lower bound
(3)
importance sampling
(2)
neural radiance field
(2)
deep generative model
(2)
posterior inference
(2)
neuro-symbolic model
(2)
approximate inference
(1)
chain-of-thought reasoning
(1)
uncertainty quantification
(1)
expectation maximization
(1)
posterior sampling
(1)
few-shot learning
(1)
3d reconstruction
(1)
scene understanding
(1)
bayesian inference
(1)
semi-supervised learning
(1)
time series
(1)
Papers
Demonstrating Arena 3.0: Advancing Social Navigation in Collaborative and Highly Dynamic Environments
RSS 2024
Doing Experiments and Revising Rules with Natural Language and Probabilistic Reasoning
NeurIPS 2024
Neural Amortized Inference for Nested Multi-Agent Reasoning
AAAI 2024
Robust Inverse Graphics via Probabilistic Inference
ICML 2024
ProbNeRF: Uncertainty-Aware Inference of 3D Shapes from 2D Images
AISTATS 2023
Training Chain-of-Thought via Latent-Variable Inference
NeurIPS 2023
Drawing out of Distribution with Neuro-Symbolic Generative Models
NeurIPS 2022
Hybrid Memoised Wake-Sleep: Approximate Inference at the Discrete-Continuous Interface
ICLR 2022
Amortized Population Gibbs Samplers with Neural Sufficient Statistics
ICML 2020
Learning to learn generative programs with Memoised Wake-Sleep
UAI 2020
Semi-supervised Sequential Generative Models
UAI 2020
Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow
UAI 2019
The Thermodynamic Variational Objective
NeurIPS 2019
Auto-Encoding Sequential Monte Carlo
ICLR 2018
Deep Variational Reinforcement Learning for POMDPs
ICML 2018
Tighter Variational Bounds are Not Necessarily Better
ICML 2018
Inference Compilation and Universal Probabilistic Programming
AISTATS 2017
Bayesian Optimization for Probabilistic Programs
NeurIPS 2016
IMI β A Multilingual Semantic Annotation Environment
ACL 2015