Rose Yu

ORCID

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 107

Top Venues

Publications

Dongxia Wu, Tsuyoshi Idé, Aurélie C. Lozano, Georgios Kollias, Jirí Navrátil, Naoki Abe, Yi-An Ma, Rose Yu
Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes. CoRR (2024)
Yasaman Jafari, Dheeraj Mekala, Rose Yu, Taylor Berg-Kirkpatrick
MORL-Prompt: An Empirical Analysis of Multi-Objective Reinforcement Learning for Discrete Prompt Optimization. CoRR (2024)
Zihao Zhou, Rose Yu
Automatic Integration for Spatiotemporal Neural Point Processes. NeurIPS (2023)
Sungduk Yu, Walter M. Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Animashree Anandkumar, Noah D. Brenowitz, Veronika Eyring, Nicholas Geneva, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Akshay Subramaniam, Carl Vondrick, Rose Yu, Laure Zanna, Tian Zheng, Ryan Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Christopher S. Bretherton, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Mark Taylor, Nathan M. Urban, Janni Yuval, Guang Zhang, Mike Pritchard
ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation. NeurIPS (2023)
Bo Zhao, Iordan Ganev, Robin Walters, Rose Yu, Nima Dehmamy
Symmetries, Flat Minima, and the Conserved Quantities of Gradient Flow. ICLR (2023)
Chen Cai, Truong Son Hy, Rose Yu, Yusu Wang
On the Connection Between MPNN and Graph Transformer. CoRR (2023)
Zihao Zhou, Rose Yu
Automatic Integration for Spatiotemporal Neural Point Processes. CoRR (2023)
Salva Rühling Cachay, Bo Zhao, Hailey James, Rose Yu
DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting. CoRR (2023)
Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Yian Ma, Rose Yu
Disentangled Multi-Fidelity Deep Bayesian Active Learning. ICML (2023)
Jianke Yang, Nima Dehmamy, Robin Walters, Rose Yu
Latent Space Symmetry Discovery. CoRR (2023)
Peter Eckmann, Jake Anderson, Michael K. Gilson, Rose Yu
Target-Free Compound Activity Prediction via Few-Shot Learning. CoRR (2023)
Mario Krenn, Lorenzo Buffoni, Bruno C. Coutinho, Sagi Eppel, Jacob Gates Foster, Andrew Gritsevskiy, Harlin Lee, Yichao Lu, João P. Moutinho, Nima Sanjabi, Rishi Sonthalia, Ngoc Mai Tran, Francisco Valente, Yangxinyu Xie, Rose Yu, Michael Kopp
Forecasting the future of artificial intelligence with machine learning-based link prediction in an exponentially growing knowledge network. Nat. Mac. Intell. 5 (11) (2023)
Abhimanyu Das, Weihao Kong, Andrew Leach, Shaan Mathur, Rajat Sen, Rose Yu
Long-term Forecasting with TiDE: Time-series Dense Encoder. CoRR (2023)
Chen Cai, Truong Son Hy, Rose Yu, Yusu Wang
On the Connection Between MPNN and Graph Transformer. ICML (2023)
Sumanth Varambally, Yi-An Ma, Rose Yu
Discovering Mixtures of Structural Causal Models from Time Series Data. CoRR (2023)
Sophia Huiwen Sun, Robin Walters, Jinxi Li, Rose Yu
Probabilistic Symmetry for Multi-Agent Dynamics. L4DC (2023)
Sungduk Yu, Walter M. Hannah, Liran Peng, Mohamed Aziz Bhouri, Ritwik Gupta, Jerry Lin, Björn Lütjens, Justus C. Will, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Anima Anandkumar, Noah D. Brenowitz, Veronika Eyring, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Carl Vondrick, Rose Yu, Laure Zanna, Ryan P. Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Gunnar Behrens, Christopher S. Bretherton, Julius J. M. Busecke, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Akshay Subramaniam, Mark A. Taylor, et al.
ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators. CoRR (2023)
Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR (2023)
Bo Zhao, Robert M. Gower, Robin Walters, Rose Yu
Improving Convergence and Generalization Using Parameter Symmetries. CoRR (2023)
Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
Deep Bayesian Active Learning for Accelerating Stochastic Simulation. KDD (2023)
Salva Rühling Cachay, Bo Zhao, Hailey Joren, Rose Yu
DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting. NeurIPS (2023)
Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Yian Ma, Rose Yu
Disentangled Multi-Fidelity Deep Bayesian Active Learning. CoRR (2023)
Alejandro Rodriguez Pascual, Ishan Mehta, Muhammad Khan, Frank Rodriz, Rose Yu
Understanding why shooters shoot - An AI-powered engine for basketball performance profiling. CoRR (2023)
Jianke Yang, Robin Walters, Nima Dehmamy, Rose Yu
Generative Adversarial Symmetry Discovery. CoRR (2023)
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
Fragile Earth: AI for Climate Sustainability - From Wildfire Disaster Management to Public Health and Beyond. KDD (2023)
Mathias Niemann Tygesen, Mayank Sharan, Francisco C. Pereira, Filipe Rodrigues, Rose Yu
Incident congestion propagation prediction using incident reports. SuMob@SIGSPATIAL (2023)
Zihao Zhou, Rose Yu
Automatic Integration for Fast and Interpretable Neural Point Processes. L4DC (2023)
Jianke Yang, Robin Walters, Nima Dehmamy, Rose Yu
Generative Adversarial Symmetry Discovery. ICML (2023)
Rui Wang, Yihe Dong, Sercan Ö. Arik, Rose Yu
Koopman Neural Operator Forecaster for Time-series with Temporal Distributional Shifts. ICLR (2023)
Mario Krenn, Qianxiang Ai, Senja Barthel, Nessa Carson, Angelo Frei, Nathan C. Frey, Pascal Friederich, Théophile Gaudin, Alberto Alexander Gayle, Kevin Maik Jablonka, Rafael F. Lameiro, Dominik Lemm, Alston Lo, Seyed Mohamad Moosavi, José Manuel Nápoles-Duarte, AkshatKumar Nigam, Robert Pollice, Kohulan Rajan, Ulrich Schatzschneider, Philippe Schwaller, Marta Skreta, Berend Smit, Felix Strieth-Kalthoff, Chong Sun, Gary Tom, Guido Falk von Rudorff, Andrew Wang, Andrew D. White, Adamo Young, Rose Yu, Alán Aspuru-Guzik
SELFIES and the future of molecular string representations. CoRR (2022)
Alan Li, Zihao Zhou, Elise Jortberg, Rose Yu
Forecasting Aortic Pressure Cross-Cohort with Deep Sequence Models. CinC (2022)
Rui Wang, Robin Walters, Rose Yu
Approximately Equivariant Networks for Imperfectly Symmetric Dynamics. ICML (2022)
Rui Wang, Robin Walters, Rose Yu
Data Augmentation vs. Equivariant Networks: A Theory of Generalization on Dynamics Forecasting. CoRR (2022)
Mario Krenn, Lorenzo Buffoni, Bruno Coutinho, Sagi Eppel, Jacob Gates Foster, Andrew Gritsevskiy, Harlin Lee, Yichao Lu, João P. Moutinho, Nima Sanjabi, Rishi Sonthalia, Ngoc Mai Tran, Francisco Valente, Yangxinyu Xie, Rose Yu, Michael Kopp
Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network. CoRR (2022)
Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
Multi-fidelity Hierarchical Neural Processes. CoRR (2022)
Sophia Sun, Robin Walters, Jinxi Li, Rose Yu
Probabilistic Symmetry for Improved Trajectory Forecasting. CoRR (2022)
Bo Zhao, Nima Dehmamy, Robin Walters, Rose Yu
Symmetry Teleportation for Accelerated Optimization. NeurIPS (2022)
Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
Multi-fidelity Hierarchical Neural Processes. KDD (2022)
Bo Zhao, Nima Dehmamy, Robin Walters, Rose Yu
Symmetry Teleportation for Accelerated Optimization. CoRR (2022)
Naoki Abe, Kathleen Buckingham, Bistra Dilkina, Emre Eftelioglu, Auroop R. Ganguly, James Hodson, Ramakrishnan Kannan, Rose Yu
Fragile Earth: AI for Climate Mitigation, Adaptation, and Environmental Justice. KDD (2022)
Bo Zhao, Iordan Ganev, Robin Walters, Rose Yu, Nima Dehmamy
Symmetries, flat minima, and the conserved quantities of gradient flow. CoRR (2022)
Zihao Zhou, Xingyi Yang, Ryan A. Rossi, Handong Zhao, Rose Yu
Neural Point Process for Learning Spatiotemporal Event Dynamics. L4DC (2022)
Sophia Sun, Rose Yu
Copula Conformal Prediction for Multi-step Time Series Forecasting. CoRR (2022)
Utkrisht Rajkumar, Sara Javadzadeh, Mihir Bafna, Dongxia Wu, Rose Yu, Jingbo Shang, Vineet Bafna
DeepViFi: detecting oncoviral infections in cancer genomes using transformers. BCB (2022)
Rui Wang, Robin Walters, Rose Yu
Meta-Learning Dynamics Forecasting Using Task Inference. NeurIPS (2022)
Rui Wang, Robin Walters, Rose Yu
Approximately Equivariant Networks for Imperfectly Symmetric Dynamics. CoRR (2022)
Rui Wang, Yihe Dong, Sercan Ö. Arik, Rose Yu
Koopman Neural Forecaster for Time Series with Temporal Distribution Shifts. CoRR (2022)
Peter Eckmann, Kunyang Sun, Bo Zhao, Mudong Feng, Michael K. Gilson, Rose Yu
LIMO: Latent Inceptionism for Targeted Molecule Generation. CoRR (2022)
Jedrzej Kozerawski, Mayank Sharan, Rose Yu
Taming the Long Tail of Deep Probabilistic Forecasting. CoRR (2022)
Peter Eckmann, Kunyang Sun, Bo Zhao, Mudong Feng, Michael K. Gilson, Rose Yu
LIMO: Latent Inceptionism for Targeted Molecule Generation. ICML (2022)
Mario Krenn, Qianxiang Ai, Senja Barthel, Nessa Carson, Angelo Frei, Nathan C. Frey, Pascal Friederich, Théophile Gaudin, Alberto Alexander Gayle, Kevin Maik Jablonka, Rafael F. Lameiro, Dominik Lemm, Alston Lo, Seyed Mohamad Moosavi, José Manuel Nápoles-Duarte, AkshatKumar Nigam, Robert Pollice, Kohulan Rajan, Ulrich Schatzschneider, Philippe Schwaller, Marta Skreta, Berend Smit, Felix Strieth-Kalthoff, Chong Sun, Gary Tom, Guido Falk von Rudorff, Andrew Wang, Andrew D. White, Adamo Young, Rose Yu, Alán Aspuru-Guzik
SELFIES and the future of molecular string representations. Patterns 3 (10) (2022)
Nima Dehmamy, Csaba Both, Jianzhi Long, Rose Yu
Faster Optimization on Sparse Graphs via Neural Reparametrization. CoRR (2022)
Rose Yu, Paris Perdikaris, Anuj Karpatne
Physics-Guided AI for Large-Scale Spatiotemporal Data. KDD (2021)
Rui Wang, Danielle C. Maddix, Christos Faloutsos, Yuyang Wang, Rose Yu
Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems. L4DC (2021)
Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
Accelerating Stochastic Simulation with Interactive Neural Processes. CoRR (2021)
Ayan Chatterjee, Omair Shafi Ahmed, Robin Walters, Zohair Shafi, Deisy Morselli Gysi, Rose Yu, Tina Eliassi-Rad, Albert-László Barabási, Giulia Menichetti
AI-Bind: Improving Binding Predictions for Novel Protein Targets and Ligands. CoRR (2021)
Rui Wang, Robin Walters, Rose Yu
Meta-Learning Dynamics Forecasting Using Task Inference. CoRR (2021)
Bijaya Adhikari, Ajitesh Srivastava, Sen Pei, Sarah Kefayati, Rose Yu, Amulya Yadav, Alexander Rodríguez, Arvind Ramanathan, Anil Vullikanti, B. Aditya Prakash
The 4th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery (epiDAMIK 4.0 @ KDD2021). KDD (2021)
Steven Wong, Lejun Jiang, Robin Walters, Tamás G. Molnár, Gábor Orosz, Rose Yu
Traffic Forecasting using Vehicle-to-Vehicle Communication. L4DC (2021)
Dongxia Wu, Liyao Gao, Matteo Chinazzi, Xinyue Xiong, Alessandro Vespignani, Yi-An Ma, Rose Yu
Quantifying Uncertainty in Deep Spatiotemporal Forecasting. KDD (2021)
Steven Wong, Lejun Jiang, Robin Walters, Tamás G. Molnár, Gábor Orosz, Rose Yu
Traffic Forecasting using Vehicle-to-Vehicle Communication. CoRR (2021)
Rui Wang, Robin Walters, Rose Yu
Incorporating Symmetry into Deep Dynamics Models for Improved Generalization. ICLR (2021)
Nima Dehmamy, Robin Walters, Yanchen Liu, Dashun Wang, Rose Yu
Automatic Symmetry Discovery with Lie Algebra Convolutional Network. NeurIPS (2021)
Robin Walters, Jinxi Li, Rose Yu
Trajectory Prediction using Equivariant Continuous Convolution. ICLR (2021)
Nima Dehmamy, Robin Walters, Yanchen Liu, Dashun Wang, Rose Yu
Automatic Symmetry Discovery with Lie Algebra Convolutional Network. CoRR (2021)
Niklas Smedemark-Margulies, Jung Yeon Park, Max Daniels, Rose Yu, Jan-Willem van de Meent, Paul Hand
Generator Surgery for Compressed Sensing. CoRR (2021)
Zihao Zhou, Xingyi Yang, Ryan A. Rossi, Handong Zhao, Rose Yu
Neural Point Process for Learning Spatiotemporal Event Dynamics. CoRR (2021)
Dongxia Wu, Liyao Gao, Xinyue Xiong, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
Quantifying Uncertainty in Deep Spatiotemporal Forecasting. CoRR (2021)
Dongxia Wu, Liyao Gao, Xinyue Xiong, Matteo Chinazzi, Alessandro Vespignani, Yian Ma, Rose Yu
DeepGLEAM: a hybrid mechanistic and deep learning model for COVID-19 forecasting. CoRR (2021)
Rui Wang, Robin Walters, Rose Yu
Incorporating Symmetry into Deep Dynamics Models for Improved Generalization. CoRR (2020)
Eliza Huang, Rui Wang, Uma Chandrasekaran, Rose Yu
Aortic Pressure Forecasting With Deep Learning. CinC (2020)
Jung Yeon Park, Kenneth Theo Carr, Stephan Zheng, Yisong Yue, Rose Yu
Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis. CoRR (2020)
Rui Wang, Karthik Kashinath, Mustafa Mustafa, Adrian Albert, Rose Yu
Towards Physics-informed Deep Learning for Turbulent Flow Prediction. KDD (2020)
Ruichao Xiao, Rose Yu
Dynamic Relational Inference in Multi-Agent Trajectories. CoRR (2020)
Chintan Shah, Nima Dehmamy, Nicola Perra, Matteo Chinazzi, Albert-László Barabási, Alessandro Vespignani, Rose Yu
Finding Patient Zero: Learning Contagion Source with Graph Neural Networks. CoRR (2020)
Rui Wang, Eliza Huang, Uma Chandrasekaran, Rose Yu
Aortic Pressure Forecasting with Deep Sequence Learning. CoRR (2020)
Armand Comas Massague, Chi Zhang, Zlatan Feric, Octavia I. Camps, Rose Yu
Learning Disentangled Representations of Video with Missing Data. CoRR (2020)
Robin Walters, Jinxi Li, Rose Yu
Trajectory Prediction using Equivariant Continuous Convolution. CoRR (2020)
Fan Xie, Alexander Chowdhury, M. Clara De Paolis Kaluza, Linfeng Zhao, Lawson L. S. Wong, Rose Yu
Deep Imitation Learning for Bimanual Robotic Manipulation. CoRR (2020)
Fan Xie, Alexander Chowdhury, M. Clara De Paolis Kaluza, Linfeng Zhao, Lawson L. S. Wong, Rose Yu
Deep Imitation Learning for Bimanual Robotic Manipulation. NeurIPS (2020)
Rui Wang, Danielle C. Maddix, Christos Faloutsos, Yuyang Wang, Rose Yu
Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems. CoRR (2020)
Armand Comas Massague, Chi Zhang, Zlatan Feric, Octavia I. Camps, Rose Yu
Learning Disentangled Representations of Videos with Missing Data. NeurIPS (2020)
Jung Yeon Park, Kenneth Theo Carr, Stephan Zheng, Yisong Yue, Rose Yu
Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis. ICML (2020)
Yukai Liu, Rose Yu, Stephan Zheng, Eric Zhan, Yisong Yue
NAOMI: Non-Autoregressive Multiresolution Sequence Imputation. NeurIPS (2019)
Nima Dehmamy, Albert-László Barabási, Rose Yu
Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology. CoRR (2019)
Rui Wang, Karthik Kashinath, Mustafa Mustafa, Adrian Albert, Rose Yu
Towards Physics-informed Deep Learning for Turbulent Flow Prediction. CoRR (2019)
Nima Dehmamy, Albert-László Barabási, Rose Yu
Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology. NeurIPS (2019)
Yukai Liu, Rose Yu, Stephan Zheng, Eric Zhan, Yisong Yue
NAOMI: Non-Autoregressive Multiresolution Sequence Imputation. CoRR (2019)
Guanya Shi, Xichen Shi, Michael O'Connell, Rose Yu, Kamyar Azizzadenesheli, Animashree Anandkumar, Yisong Yue, Soon-Jo Chung
Neural Lander: Stable Drone Landing Control Using Learned Dynamics. ICRA (2019)
Stephan Zheng, Rose Yu, Yisong Yue
Multi-resolution Tensor Learning for Large-Scale Spatial Data. CoRR (2018)
Rose Yu, Max Guangyu Li, Yan Liu
Tensor Regression Meets Gaussian Processes. AISTATS (2018)
Sung-En Chang, Xun Zheng, Ian En-Hsu Yen, Pradeep Ravikumar, Rose Yu
Learning Tensor Latent Features. CoRR (2018)
Yaguang Li, Rose Yu, Cyrus Shahabi, Yan Liu
Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. ICLR (Poster) (2018)
Guanya Shi, Xichen Shi, Michael O'Connell, Rose Yu, Kamyar Azizzadenesheli, Animashree Anandkumar, Yisong Yue, Soon-Jo Chung
Neural Lander: Stable Drone Landing Control using Learned Dynamics. CoRR (2018)
Rose Yu, Stephan Zheng, Anima Anandkumar, Yisong Yue
Long-term Forecasting using Tensor-Train RNNs. CoRR (2017)
Rose Yu, Max Guangyu Li, Yan Liu
Tensor Regression Meets Gaussian Processes. CoRR (2017)
Yaguang Li, Rose Yu, Cyrus Shahabi, Yan Liu
Graph Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. CoRR (2017)
Rose Yu, Yaguang Li, Cyrus Shahabi, Ugur Demiryurek, Yan Liu
Deep Learning: A Generic Approach for Extreme Condition Traffic Forecasting. SDM (2017)
Rose Yu, Andrew Gelfand, Suju Rajan, Cyrus Shahabi, Yan Liu
Geographic Segmentation via Latent Poisson Factor Model. WSDM (2016)
Rose Yu, Yan Liu
Learning from Multiway Data: Simple and Efficient Tensor Regression. ICML (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Rose Yu