| 2026 | ACL | CaTS-Bench: Can Language Models Describe Time Series? | Luca Zhou, Pratham Yashwante, Marshall Fisher, Alessio Sampieri, Zihao Zhou, Fabio Galasso, Rose Yu |
| 2025 | ICLR | ClimaQA: An Automated Evaluation Framework for Climate Question Answering Models. | Veeramakali Vignesh Manivannan, Yasaman Jafari, Srikar Eranky, Spencer Ho, Rose Yu, Duncan Watson-Parris, Yian Ma, Leon Bergen, Taylor Berg-Kirkpatrick |
| 2025 | ICLR | Can LLMs Understand Time Series Anomalies? | Zihao Zhou, Rose Yu |
| 2025 | ICML | Adapting While Learning: Grounding LLMs for Scientific Problems with Tool Usage Adaptation. | Bohan Lyu, Yadi Cao, Duncan Watson-Parris, Leon Bergen, Taylor Berg-Kirkpatrick, Rose Yu |
| 2025 | ICML | Understanding Mode Connectivity via Parameter Space Symmetry. | Bo Zhao, Nima Dehmamy, Robin Walters, Rose Yu |
| 2025 | ICML | AtlasD: Automatic Local Symmetry Discovery. | Manu Bhat, Jonghyun Park, Jianke Yang, Nima Dehmamy, Robin Walters, Rose Yu |
| 2025 | ICML | MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning. | Peter Eckmann, Dongxia Wu, Germano Heinzelmann, Michael K. Gilson, Rose Yu |
| 2025 | ICML | Discovering Latent Causal Graphs from Spatiotemporal Data. | Kun Wang, Sumanth Varambally, Duncan Watson-Parris, Yian Ma, Rose Yu |
| 2024 | AISTATS | Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes. | Dongxia Wu, Tsuyoshi Id, Georgios Kollias, Jir Navrtil, Aurlie C. Lozano, Naoki Abe, Yi-An Ma, Rose Yu |
| 2024 | AISTATS | On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers. | Cai Zhou, Rose Yu, Yusu Wang |
| 2024 | EMNLP | MORL-Prompt: An Empirical Analysis of Multi-Objective Reinforcement Learning for Discrete Prompt Optimization. | Yasaman Jafari, Dheeraj Mekala, Rose Yu, Taylor Berg-Kirkpatrick |
| 2024 | ICLR | Copula Conformal prediction for multi-step time series prediction. | Sophia Huiwen Sun, Rose Yu |
| 2024 | ICLR | Improving Convergence and Generalization Using Parameter Symmetries. | Bo Zhao, Robert M. Gower, Robin Walters, Rose Yu |
| 2024 | ICML | Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling. | Ruijia Niu, Dongxia Wu, Kai Kim, Yian Ma, Duncan Watson-Parris, Rose Yu |
| 2024 | ICML | Discovering Mixtures of Structural Causal Models from Time Series Data. | Sumanth Varambally, Yian Ma, Rose Yu |
| 2024 | ICML | Latent Space Symmetry Discovery. | Jianke Yang, Nima Dehmamy, Robin Walters, Rose Yu |
| 2023 | ICLR | Koopman Neural Operator Forecaster for Time-series with Temporal Distributional Shifts. | Rui Wang, Yihe Dong, Sercan . Arik, Rose Yu |
| 2023 | ICLR | Symmetries, Flat Minima, and the Conserved Quantities of Gradient Flow. | Bo Zhao, Iordan Ganev, Robin Walters, Rose Yu, Nima Dehmamy |
| 2023 | ICML | On the Connection Between MPNN and Graph Transformer. | Chen Cai, Truong Son Hy, Rose Yu, Yusu Wang |
| 2023 | ICML | Disentangled Multi-Fidelity Deep Bayesian Active Learning. | Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Yi-An Ma, Rose Yu |
| 2023 | ICML | Generative Adversarial Symmetry Discovery. | Jianke Yang, Robin Walters, Nima Dehmamy, Rose Yu |
| 2023 | KDD | Fragile Earth: AI for Climate Sustainability - From Wildfire Disaster Management to Public Health and Beyond. | Naoki Abe, Kathleen Buckingham, Yuzhou Chen, Bistra Dilkina, Emre Eftelioglu, Auroop R. Ganguly, Yulia R. Gel, James Hodson, Ramakrishnan Kannan, Huikyo Lee, Jiafu Mao, Rose Yu |
| 2023 | KDD | Deep Bayesian Active Learning for Accelerating Stochastic Simulation. | Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu |
| 2022 | ICML | LIMO: Latent Inceptionism for Targeted Molecule Generation. | Peter Eckmann, Kunyang Sun, Bo Zhao, Mudong Feng, Michael K. Gilson, Rose Yu |
| 2022 | ICML | Approximately Equivariant Networks for Imperfectly Symmetric Dynamics. | Rui Wang, Robin Walters, Rose Yu |
| 2022 | KDD | Fragile Earth: AI for Climate Mitigation, Adaptation, and Environmental Justice. | Naoki Abe, Kathleen Buckingham, Bistra Dilkina, Emre Eftelioglu, Auroop R. Ganguly, James Hodson, Ramakrishnan Kannan, Rose Yu |
| 2022 | KDD | Multi-fidelity Hierarchical Neural Processes. | Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu |
| 2021 | ICLR | Trajectory Prediction using Equivariant Continuous Convolution. | Robin Walters, Jinxi Li, Rose Yu |
| 2021 | ICLR | Incorporating Symmetry into Deep Dynamics Models for Improved Generalization. | Rui Wang, Robin Walters, Rose Yu |
| 2021 | KDD | The 4th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery (epiDAMIK 4.0 @ KDD2021). | Bijaya Adhikari, Ajitesh Srivastava, Sen Pei, Sarah Kefayati, Rose Yu, Amulya Yadav, Alexander Rodrguez, Arvind Ramanathan, Anil Vullikanti, B. Aditya Prakash |
| 2021 | KDD | Quantifying Uncertainty in Deep Spatiotemporal Forecasting. | Dongxia Wu, Liyao Gao, Matteo Chinazzi, Xinyue Xiong, Alessandro Vespignani, Yi-An Ma, Rose Yu |
| 2021 | KDD | Physics-Guided AI for Large-Scale Spatiotemporal Data. | Rose Yu, Paris Perdikaris, Anuj Karpatne |
| 2020 | ICML | Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis. | Jung Yeon Park, Kenneth Theo Carr, Stephan Zheng, Yisong Yue, Rose Yu |
| 2020 | KDD | Towards Physics-informed Deep Learning for Turbulent Flow Prediction. | Rui Wang, Karthik Kashinath, Mustafa Mustafa, Adrian Albert, Rose Yu |
| 2019 | ICRA | Neural Lander: Stable Drone Landing Control Using Learned Dynamics. | Guanya Shi, Xichen Shi, Michael O'Connell, Rose Yu, Kamyar Azizzadenesheli, Animashree Anandkumar, Yisong Yue, Soon-Jo Chung |
| 2018 | AISTATS | Tensor Regression Meets Gaussian Processes. | Rose Yu, Max Guangyu Li, Yan Liu |
| 2018 | ICLR | Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. | Yaguang Li, Rose Yu, Cyrus Shahabi, Yan Liu |
| 2017 | SDM | Deep Learning: A Generic Approach for Extreme Condition Traffic Forecasting. | Rose Yu, Yaguang Li, Cyrus Shahabi, Ugur Demiryurek, Yan Liu |
| 2016 | ICML | Learning from Multiway Data: Simple and Efficient Tensor Regression. | Rose Yu, Yan Liu |
| 2016 | KDD | Latent Space Model for Road Networks to Predict Time-Varying Traffic. | Dingxiong Deng, Cyrus Shahabi, Ugur Demiryurek, Linhong Zhu, Rose Yu, Yan Liu |
| 2016 | WSDM | Geographic Segmentation via Latent Poisson Factor Model. | Rose Yu, Andrew Gelfand, Suju Rajan, Cyrus Shahabi, Yan Liu |
| 2015 | ICML | Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams. | Rose Yu, Dehua Cheng, Yan Liu |