Yuanqi Du
25 papers · 2020–2025 · 7 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (56) 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
(2)
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Renaissance Researcher
(9)
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Century Club Β· Bronze
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Research topics
Machine Learning
(20)
Deep Learning
(16)
Core Methods
(11)
Optimization & Theory
(10)
Models
(9)
Artificial Intelligence
(8)
Architectures
(7)
Core AI
(7)
Application Areas
(6)
Mathematics & Optimization
(5)
Learning Types Β· Deep Learning
(4)
Optimization
(4)
Computer Vision
(3)
Bayesian & Probabilistic
(3)
Learning Types Β· Machine Learning
(3)
Keywords
graph neural network
(4)
geometric deep learning
(3)
generative model
(3)
variational inference
(3)
molecular representation
(3)
disentangled representation
(3)
molecular simulation
(2)
black-box optimization
(2)
molecular dynamics
(2)
deep generative model
(2)
transition path sampling
(2)
large language model
(2)
drug design
(2)
property control
(2)
diffusion model
(2)
drug discovery
(2)
chemical space
(2)
graph representation learning
(1)
self-supervised learning
(1)
optimal transport
(1)
Papers
Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints
AISTATS 2025
Efficient Evolutionary Search Over Chemical Space with Large Language Models
ICLR 2025
Graph Generative Pre-trained Transformer
ICML 2025
LLM-Augmented Chemical Synthesis and Design Decision Programs
ICML 2025
Aligning Large Language Models with Representation Editing: A Control Perspective
NeurIPS 2024
Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling
NeurIPS 2024
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks
ICLR 2024
Navigating Chemical Space with Latent Flows
NeurIPS 2024
A Flexible Diffusion Model
ICML 2023
A new perspective on building efficient and expressive 3D equivariant graph neural networks
NeurIPS 2023
A Systematic Survey of Chemical Pre-trained Models
IJCAI 2023
GAUCHE: A Library for Gaussian Processes in Chemistry
NeurIPS 2023
M$^2$Hub: Unlocking the Potential of Machine Learning for Materials Discovery
NeurIPS 2023
On Separate Normalization in Self-supervised Transformers
NeurIPS 2023
Pik-Fix: Restoring and Colorizing Old Photos
WACV 2023
Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths
NeurIPS 2023
Uncovering Neural Scaling Laws in Molecular Representation Learning
NeurIPS 2023
Weighted Sampling without Replacement for Deep Top-k Classification
ICML 2023
Audio-Driven Co-Speech Gesture Video Generation
NeurIPS 2022
Disentangled Spatiotemporal Graph Generative Models
AAAI 2022
Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks
NeurIPS 2022
Multi-objective Deep Data Generation with Correlated Property Control
NeurIPS 2022
SE(3) Equivariant Graph Neural Networks with Complete Local Frames
ICML 2022
Property Controllable Variational Autoencoder via Invertible Mutual Dependence
ICLR 2021
American Sign Language Recognition Using an FMCW Wireless Sensor (Student Abstract)
AAAI 2020