2024
Ligand-Based Compound Activity Prediction via Few-Shot Learning.
J. Chem. Inf. Model., 2024
VICON: Vision In-Context Operator Networks for Multi-Physics Fluid Dynamics Prediction.
CoRR, 2024
Multi-Modal Forecaster: Jointly Predicting Time Series and Textual Data.
CoRR, 2024
Discovering Latent Structural Causal Models from Spatio-Temporal Data.
CoRR, 2024
Adapting While Learning: Grounding LLMs for Scientific Problems with Intelligent Tool Usage Adaptation.
CoRR, 2024
ClimaQA: An Automated Evaluation Framework for Climate Foundation Models.
CoRR, 2024
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning.
CoRR, 2024
Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs.
CoRR, 2024
Can LLMs Understand Time Series Anomalies?
CoRR, 2024
Back to Bayesics: Uncovering Human Mobility Distributions and Anomalies with an Integrated Statistical and Neural Framework.
CoRR, 2024
Technical report: Improving the properties of molecules generated by LIMO.
CoRR, 2024
Diff-BBO: Diffusion-Based Inverse Modeling for Black-Box Optimization.
CoRR, 2024
Probabilistic Emulation of a Global Climate Model with Spherical DYffusion.
CoRR, 2024
MFBind: a Multi-Fidelity Approach for Evaluating Drug Compounds in Practical Generative Modeling.
CoRR, 2024
Symmetry-Informed Governing Equation Discovery.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Probablistic Emulation of a Global Climate Model with Spherical DYffusion.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Understanding the difficulty of solving Cauchy problems with PINNs.
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024
Data-driven simulator for mechanical circulatory support with domain adversarial neural process.
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024
Latent Space Symmetry Discovery.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Discovering Mixtures of Structural Causal Models from Time Series Data.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Improving Convergence and Generalization Using Parameter Symmetries.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Copula Conformal prediction for multi-step time series prediction.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
MORL-Prompt: An Empirical Analysis of Multi-Objective Reinforcement Learning for Discrete Prompt Optimization.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
2023
Forecasting the future of artificial intelligence with machine learning-based link prediction in an exponentially growing knowledge network.
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
Nat. Mac. Intell., October, 2023
Long-term Forecasting with TiDE: Time-series Dense Encoder.
Trans. Mach. Learn. Res., 2023
Target-Free Compound Activity Prediction via Few-Shot Learning.
CoRR, 2023
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems.
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
CoRR, 2023
ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators.
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
et al.
CoRR, 2023
DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting.
CoRR, 2023
Understanding why shooters shoot - An AI-powered engine for basketball performance profiling.
CoRR, 2023
Incident congestion propagation prediction using incident reports.
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Sustainable Mobility, 2023
Automatic Integration for Spatiotemporal Neural Point Processes.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation.
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Automatic Integration for Fast and Interpretable Neural Point Processes.
Proceedings of the Learning for Dynamics and Control Conference, 2023
Probabilistic Symmetry for Multi-Agent Dynamics.
Proceedings of the Learning for Dynamics and Control Conference, 2023
Deep Bayesian Active Learning for Accelerating Stochastic Simulation.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Fragile Earth: AI for Climate Sustainability - From Wildfire Disaster Management to Public Health and Beyond.
,
,
,
,
,
,
,
,
,
,
,
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Generative Adversarial Symmetry Discovery.
Proceedings of the International Conference on Machine Learning, 2023
Disentangled Multi-Fidelity Deep Bayesian Active Learning.
Proceedings of the International Conference on Machine Learning, 2023
On the Connection Between MPNN and Graph Transformer.
Proceedings of the International Conference on Machine Learning, 2023
Symmetries, Flat Minima, and the Conserved Quantities of Gradient Flow.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Koopman Neural Operator Forecaster for Time-series with Temporal Distributional Shifts.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
2022
SELFIES and the future of molecular string representations.
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
Patterns, 2022
Copula Conformal Prediction for Multi-step Time Series Forecasting.
CoRR, 2022
Koopman Neural Forecaster for Time Series with Temporal Distribution Shifts.
CoRR, 2022
Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network.
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
CoRR, 2022
Data Augmentation vs. Equivariant Networks: A Theory of Generalization on Dynamics Forecasting.
CoRR, 2022
Faster Optimization on Sparse Graphs via Neural Reparametrization.
CoRR, 2022
Probabilistic Symmetry for Improved Trajectory Forecasting.
CoRR, 2022
Taming the Long Tail of Deep Probabilistic Forecasting.
CoRR, 2022
Symmetry Teleportation for Accelerated Optimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Meta-Learning Dynamics Forecasting Using Task Inference.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Neural Point Process for Learning Spatiotemporal Event Dynamics.
Proceedings of the Learning for Dynamics and Control Conference, 2022
Multi-fidelity Hierarchical Neural Processes.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
Fragile Earth: AI for Climate Mitigation, Adaptation, and Environmental Justice.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
Approximately Equivariant Networks for Imperfectly Symmetric Dynamics.
Proceedings of the International Conference on Machine Learning, 2022
LIMO: Latent Inceptionism for Targeted Molecule Generation.
Proceedings of the International Conference on Machine Learning, 2022
Forecasting Aortic Pressure Cross-Cohort with Deep Sequence Models.
Proceedings of the Computing in Cardiology, 2022
DeepViFi: detecting oncoviral infections in cancer genomes using transformers.
Proceedings of the BCB '22: 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Northbrook, Illinois, USA, August 7, 2022
2021
AI-Bind: Improving Binding Predictions for Novel Protein Targets and Ligands.
CoRR, 2021
Accelerating Stochastic Simulation with Interactive Neural Processes.
CoRR, 2021
Generator Surgery for Compressed Sensing.
CoRR, 2021
DeepGLEAM: a hybrid mechanistic and deep learning model for COVID-19 forecasting.
CoRR, 2021
Automatic Symmetry Discovery with Lie Algebra Convolutional Network.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Traffic Forecasting using Vehicle-to-Vehicle Communication.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021
Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021
Physics-Guided AI for Large-Scale Spatiotemporal Data.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
Quantifying Uncertainty in Deep Spatiotemporal Forecasting.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
The 4th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery (epiDAMIK 4.0 @ KDD2021).
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
Incorporating Symmetry into Deep Dynamics Models for Improved Generalization.
Proceedings of the 9th International Conference on Learning Representations, 2021
Trajectory Prediction using Equivariant Continuous Convolution.
Proceedings of the 9th International Conference on Learning Representations, 2021
2020
Dynamic Relational Inference in Multi-Agent Trajectories.
CoRR, 2020
Learning Disentangled Representations of Video with Missing Data.
CoRR, 2020
Finding Patient Zero: Learning Contagion Source with Graph Neural Networks.
CoRR, 2020
Aortic Pressure Forecasting with Deep Sequence Learning.
CoRR, 2020
Learning Disentangled Representations of Videos with Missing Data.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Deep Imitation Learning for Bimanual Robotic Manipulation.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Towards Physics-informed Deep Learning for Turbulent Flow Prediction.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020
Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis.
Proceedings of the 37th International Conference on Machine Learning, 2020
Aortic Pressure Forecasting With Deep Learning.
Proceedings of the Computing in Cardiology, 2020
2019
NAOMI: Non-Autoregressive Multiresolution Sequence Imputation.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Neural Lander: Stable Drone Landing Control Using Learned Dynamics.
Proceedings of the International Conference on Robotics and Automation, 2019
2018
Learning Tensor Latent Features.
CoRR, 2018
Multi-resolution Tensor Learning for Large-Scale Spatial Data.
CoRR, 2018
Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting.
Proceedings of the 6th International Conference on Learning Representations, 2018
Tensor Regression Meets Gaussian Processes.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
2017
Spatiotemporal Analysis of Social Media Data.
Proceedings of the Encyclopedia of GIS., 2017
Long-term Forecasting using Tensor-Train RNNs.
CoRR, 2017
Graph Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting.
CoRR, 2017
Deep Learning: A Generic Approach for Extreme Condition Traffic Forecasting.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017
2016
A Survey on Social Media Anomaly Detection.
SIGKDD Explor., 2016
Geographic Segmentation via Latent Poisson Factor Model.
Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, 2016
Latent Space Model for Road Networks to Predict Time-Varying Traffic.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016
Learning from Multiway Data: Simple and Efficient Tensor Regression.
Proceedings of the 33nd International Conference on Machine Learning, 2016
2015
GLAD: Group Anomaly Detection in Social Media Analysis.
ACM Trans. Knowl. Discov. Data, 2015
Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams.
Proceedings of the 32nd International Conference on Machine Learning, 2015
2014
Fast Multivariate Spatio-temporal Analysis via Low Rank Tensor Learning.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
2011
A Feasible Nonconvex Relaxation Approach to Feature Selection.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011