Yuanqi Du
25 papers · 2020–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (7) πΊοΈ Taxonomy Completionist (10) π§ Keyword Pioneer π Interdisciplinary Bridge π Academic Marathon (5)
π£
Hot Topic Early Bird
π§
Keyword Pioneer
π
Interdisciplinary Bridge
π
Keyword Champion
(2)
π±
Topic Pioneer
π₯
Mega-Team
(28)
π
Grand Slam
ποΈ
Keyword Collector
(122)
π
Century Club
(25)
π₯
Unstoppable
(6)
β‘
Prolific Year
(5)
Conferences
NIPS (12)
ICML (5)
ICLR (3)
AAAI (2)
AISTATS (1)
IJCAI (1)
WACV (1)
Top co-authors
Keywords
generative model
(3)
geometric deep learning
(3)
graph neural network
(3)
variational inference
(3)
drug design
(2)
drug discovery
(2)
molecular representation
(2)
molecular simulation
(2)
disentangled representation
(2)
transition path sampling
(2)
molecular dynamics
(2)
deep generative model
(2)
graph generation
(1)
image restoration
(1)
image synthesis
(1)
graph representation learning
(1)
bayesian learning
(1)
reinforcement learning
(1)
self-supervised learning
(1)
network analysis
(1)
Papers
LLM-Augmented Chemical Synthesis and Design Decision Programs
ICML 2025
Efficient Evolutionary Search Over Chemical Space with Large Language Models
ICLR 2025
Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints
AISTATS 2025
Graph Generative Pre-trained Transformer
ICML 2025
Aligning Large Language Models with Representation Editing: A Control Perspective
NIPS 2024
Navigating Chemical Space with Latent Flows
NIPS 2024
Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling
NIPS 2024
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks
ICLR 2024
Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths
NIPS 2023
On Separate Normalization in Self-supervised Transformers
NIPS 2023
A Systematic Survey of Chemical Pre-trained Models
IJCAI 2023
A Flexible Diffusion Model
ICML 2023
Pik-Fix: Restoring and Colorizing Old Photos
WACV 2023
Uncovering Neural Scaling Laws in Molecular Representation Learning
NIPS 2023
Weighted Sampling without Replacement for Deep Top-$k$ Classification
ICML 2023
A new perspective on building efficient and expressive 3D equivariant graph neural networks
NIPS 2023
GAUCHE: A Library for Gaussian Processes in Chemistry
NIPS 2023
M$^2$Hub: Unlocking the Potential of Machine Learning for Materials Discovery
NIPS 2023
Audio-Driven Co-Speech Gesture Video Generation
NIPS 2022
Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks
NIPS 2022
Multi-objective Deep Data Generation with Correlated Property Control
NIPS 2022
Disentangled Spatiotemporal Graph Generative Models
AAAI 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