Yuanqi Du

According to our database1, Yuanqi Du authored at least 57 papers between 2020 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Molecular Contrastive Pretraining with Collaborative Featurizations.
J. Chem. Inf. Model., February, 2024

Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints.
CoRR, 2024

2023
ChemSpacE: Interpretable and Interactive Chemical Space Exploration.
Trans. Mach. Learn. Res., 2023

Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model.
Nat. Comput. Sci., 2023

Scientific discovery in the age of artificial intelligence.
Nat., 2023

Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks.
CoRR, 2023

Uncovering Neural Scaling Laws in Molecular Representation Learning.
CoRR, 2023

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems.
CoRR, 2023

MUBen: Benchmarking the Uncertainty of Pre-Trained Models for Molecular Property Prediction.
CoRR, 2023

Xtal2DoS: Attention-based Crystal to Sequence Learning for Density of States Prediction.
CoRR, 2023

Pik-Fix: Restoring and Colorizing Old Photos.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023


M<sup>2</sup>Hub: Unlocking the Potential of Machine Learning for Materials Discovery.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A new perspective on building efficient and expressive 3D equivariant graph neural networks.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On Separate Normalization in Self-supervised Transformers.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Uncovering Neural Scaling Laws in Molecular Representation Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Systematic Survey of Chemical Pre-trained Models.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

A Flexible Diffusion Model.
Proceedings of the International Conference on Machine Learning, 2023

Weighted Sampling without Replacement for Deep Top-k Classification.
Proceedings of the International Conference on Machine Learning, 2023

2022
GAUCHE: A Library for Gaussian Processes in Chemistry.
CoRR, 2022

A Systematic Survey of Molecular Pre-trained Models.
CoRR, 2022

Structure-based Drug Design with Equivariant Diffusion Models.
CoRR, 2022

Improving Molecular Pretraining with Complementary Featurizations.
CoRR, 2022

Controllable Data Generation by Deep Learning: A Review.
CoRR, 2022

Path Integral Stochastic Optimal Control for Sampling Transition Paths.
CoRR, 2022

Pik-Fix: Restoring and Colorizing Old Photos.
CoRR, 2022

MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design.
CoRR, 2022

Recovering medical images from CT film photos.
CoRR, 2022

A Survey of Pretraining on Graphs: Taxonomy, Methods, and Applications.
CoRR, 2022

Small molecule generation via disentangled representation learning.
Bioinform., 2022

Interpretable Molecular Graph Generation via Monotonic Constraints.
Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Multi-objective Deep Data Generation with Correlated Property Control.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Audio-Driven Co-Speech Gesture Video Generation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022


A Survey on Deep Graph Generation: Methods and Applications.
Proceedings of the Learning on Graphs Conference, 2022

Semi-Supervised Pseudo-Healthy Image Synthesis via Confidence Augmentation.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

SE(3) Equivariant Graph Neural Networks with Complete Local Frames.
Proceedings of the International Conference on Machine Learning, 2022

Property-Controllable Generation of Quaternary Ammonium Compounds.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

Disentangled Spatiotemporal Graph Generative Models.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Dataset for Disentangled Representation Learning for Interpretable Molecule Generation.
Dataset, April, 2021

Dataset for Generative Adversarial Learning of Protein Tertiary Structures. Molecules, 2021.
Dataset, February, 2021

Graph-based Ensemble Machine Learning for Student Performance Prediction.
CoRR, 2021

Equivariant vector field network for many-body system modeling.
CoRR, 2021

Physics-Augmented Learning: A New Paradigm Beyond Physics-Informed Learning.
CoRR, 2021

Where is the disease? Semi-supervised pseudo-normality synthesis from an abnormal image.
CoRR, 2021

Deep learning to segment pelvic bones: large-scale CT datasets and baseline models.
Int. J. Comput. Assist. Radiol. Surg., 2021

GraphGT: Machine Learning Datasets for Graph Generation and Transformation.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Deep Generative Models for Spatial Networks.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Property Controllable Variational Autoencoder via Invertible Mutual Dependence.
Proceedings of the 9th International Conference on Learning Representations, 2021

Graph Representation Learning for Protein Conformation Sampling.
Proceedings of the Computational Advances in Bio and Medical Sciences: 11th International Conference, 2021

Ensemble Machine Learning System for Student AcademicPerformance Prediction.
Proceedings of the Joint Proceedings of the Workshops at the International Conference on Educational Data Mining 2021 co-located with 14th International Conference on Educational Data Mining (EDM 2021), 2021

Deep Latent-Variable Models for Controllable Molecule Generation.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

2020
CT Film Recovery via Disentangling Geometric Deformation and Illumination Variation: Simulated Datasets and Deep Models.
CoRR, 2020

Expressive ASL Recognition using Millimeter-wave Wireless Signals.
Proceedings of the 17th Annual IEEE International Conference on Sensing, 2020

American Sign Language Recognition Using an FMCW Wireless Sensor (Student Abstract).
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020


  Loading...