← Authors

Rose Yu

50 papers · 2015–2025 · 7 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (20) πŸƒ Academic Marathon (10) 🧭 Keyword Pioneer 🌍 Conference Polyglot (7) 🐝 Cross-Pollinator (14) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge 🀝 Dynamic Duo (15) πŸ‘‘ Triple Crown 🌱 Topic Pioneer πŸ† Keyword Champion (3) πŸ‘₯ Mega-Team (56) πŸ”¬ Deep Specialist (13) πŸš€ Conference Pioneer ⚑ Prolific Year (5) πŸ”₯ Unstoppable (8) πŸ—ƒοΈ Keyword Collector (171) ❓ The Questioner πŸ“ˆ Trend Setter πŸ’Ž Century Club (50)

Conferences

ICML (16) NIPS (12) ICLR (9) L4DC (8) AISTATS (3) EMNLP (1) JMLR (1)

Top co-authors

Robin Walters (15) Nima Dehmamy (9) Bo Zhao (7) Yian Ma (6) Rui Wang (5) Zihao Zhou (5) Yan Liu (4) Duncan Watson-Parris (4) Dongxia Wu (4) Jianke Yang (4)

Research topics

Machine Learning (1) Science (1)

Keywords

neural network (3) equivariant neural network (3) tensor decomposition (3) intensity function (3) generative model (3) spatiotemporal point process (2) neural point process (2) automatic integration (2) physics-based model (2) approximation theory (2) symmetry discovery (2) graph convolutional network (2) disentangled representation (2) multiresolution learning (2) diffusion model (2) partial differential equation (2) deep learning (2) dynamical system (2) graph transformer (2) lie algebra (2)

Papers

Adapting While Learning: Grounding LLMs for Scientific Problems with Tool Usage Adaptation ICML 2025
BIGE : Biomechanics-informed GenAI for Exercise Science L4DC 2025
Can LLMs Understand Time Series Anomalies? ICLR 2025
ClimaQA: An Automated Evaluation Framework for Climate Question Answering Models ICLR 2025
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning ICML 2025
AtlasD: Automatic Local Symmetry Discovery ICML 2025
Understanding Mode Connectivity via Parameter Space Symmetry ICML 2025
Discovering Latent Causal Graphs from Spatiotemporal Data ICML 2025
ClimSim-Online: A Large Multi-Scale Dataset and Framework for Hybrid Physics-ML Climate Emulation JMLR 2025
MORL-Prompt: An Empirical Analysis of Multi-Objective Reinforcement Learning for Discrete Prompt Optimization EMNLP 2024
Latent Space Symmetry Discovery ICML 2024
Discovering Mixtures of Structural Causal Models from Time Series Data ICML 2024
Symmetry-Informed Governing Equation Discovery NIPS 2024
Copula Conformal prediction for multi-step time series prediction ICLR 2024
Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling ICML 2024
Data-driven simulator for mechanical circulatory support with domain adversarial neural process L4DC 2024
Understanding the difficulty of solving Cauchy problems with PINNs L4DC 2024
Improving Convergence and Generalization Using Parameter Symmetries ICLR 2024
Probablistic Emulation of a Global Climate Model with Spherical DYffusion NIPS 2024
Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes AISTATS 2024
On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers AISTATS 2024
Symmetries, Flat Minima, and the Conserved Quantities of Gradient Flow ICLR 2023
ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation NIPS 2023
DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting NIPS 2023
Automatic Integration for Spatiotemporal Neural Point Processes NIPS 2023
Koopman Neural Operator Forecaster for Time-series with Temporal Distributional Shifts ICLR 2023
On the Connection Between MPNN and Graph Transformer ICML 2023
Disentangled Multi-Fidelity Deep Bayesian Active Learning ICML 2023
Generative Adversarial Symmetry Discovery ICML 2023
Automatic Integration for Fast and Interpretable Neural Point Processes L4DC 2023
Probabilistic Symmetry for Multi-Agent Dynamics L4DC 2023
LIMO: Latent Inceptionism for Targeted Molecule Generation ICML 2022
Neural Point Process for Learning Spatiotemporal Event Dynamics L4DC 2022
Approximately Equivariant Networks for Imperfectly Symmetric Dynamics ICML 2022
Meta-Learning Dynamics Forecasting Using Task Inference NIPS 2022
Symmetry Teleportation for Accelerated Optimization NIPS 2022
Incorporating Symmetry into Deep Dynamics Models for Improved Generalization ICLR 2021
Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems L4DC 2021
Trajectory Prediction using Equivariant Continuous Convolution ICLR 2021
Automatic Symmetry Discovery with Lie Algebra Convolutional Network NIPS 2021
Traffic Forecasting using Vehicle-to-Vehicle Communication L4DC 2021
Deep Imitation Learning for Bimanual Robotic Manipulation NIPS 2020
Learning Disentangled Representations of Videos with Missing Data NIPS 2020
Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis ICML 2020
Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology NIPS 2019
NAOMI: Non-Autoregressive Multiresolution Sequence Imputation NIPS 2019
Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting ICLR 2018
Tensor Regression Meets Gaussian Processes AISTATS 2018
Learning from Multiway Data: Simple and Efficient Tensor Regression ICML 2016
Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams ICML 2015