Alan Aspuru-Guzik
17 papers · 2015–2026 · 6 venues · across top CS/AI venues
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Research topics
Machine Learning
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Optimization & Theory
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chemical space exploration
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large language model
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material recognition
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bayesian optimization
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neural network
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molecular discovery
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black-box optimization
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few-shot learning
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zero-shot learning
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computer vision
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parameter estimation
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uncertainty quantification
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logical reasoning
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optimal transport
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image restoration
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feature learning
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quantum machine learning
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Papers
From Global to Factor-Wise Expert Composition in Discrete Diffusion Models
UAI 2026
AnyPlace: Learning Generalizable Object Placement for Robot Manipulation
CoRL 2025
Efficient Evolutionary Search Over Chemical Space with Large Language Models
ICLR 2025
Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts
ICML 2025
Stiefel Flow Matching for Moment-Constrained Structure Elucidation
ICLR 2025
A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?
ICML 2024
Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling
NeurIPS 2024
Infusing Synthetic Data with Real-World Patterns for Zero-Shot Material State Segmentation
NeurIPS 2024
Position: Application-Driven Innovation in Machine Learning
ICML 2024
Quantum Deep Equilibrium Models
NeurIPS 2024
GAUCHE: A Library for Gaussian Processes in Chemistry
NeurIPS 2023
One-Shot Recognition of Any Material Anywhere Using Contrastive Learning with Physics-Based Rendering
ICCV 2023
Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design
NeurIPS 2023
Seeing Glass: Joint Point-Cloud and Depth Completion for Transparent Objects
CoRL 2021
Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space
ICLR 2020
Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space
ICML 2017
Convolutional Networks on Graphs for Learning Molecular Fingerprints
NeurIPS 2015