Chris Cundy
Chris Cundy
University of Stanford
Verified email at - Homepage
Cited by
Cited by
Iq-learn: Inverse soft-q learning for imitation
D Garg, S Chakraborty, C Cundy, J Song, S Ermon
Advances in Neural Information Processing Systems 34, 4028-4039, 2021
On the opportunities and challenges of foundation models for geospatial artificial intelligence
G Mai, W Huang, J Sun, S Song, D Mishra, N Liu, S Gao, T Liu, G Cong, ...
arXiv preprint arXiv:2304.06798, 2023
Neural networks and the chomsky hierarchy
G Delétang, A Ruoss, J Grau-Moya, T Genewein, LK Wenliang, E Catt, ...
arXiv preprint arXiv:2207.02098, 2022
Parallelizing Linear Recurrent Neural Nets Over Sequence Length
E Martin, C Cundy
International Conference on Learning Representations (ICLR) 2018, 2018
BCD nets: Scalable variational approaches for bayesian causal discovery
C Cundy, A Grover, S Ermon
Advances in Neural Information Processing Systems 34, 7095-7110, 2021
Towards a foundation model for geospatial artificial intelligence (vision paper)
G Mai, C Cundy, K Choi, Y Hu, N Lao, S Ermon
Proceedings of the 30th International Conference on Advances in Geographic …, 2022
Geo-knowledge-guided GPT models improve the extraction of location descriptions from disaster-related social media messages
Y Hu, G Mai, C Cundy, K Choi, N Lao, W Liu, G Lakhanpal, RZ Zhou, ...
International Journal of Geographical Information Science 37 (11), 2289-2318, 2023
Simulation of plants in buildings; incorporating plant-Air interactions in building energy simulation
R Ward, R Choudhary, C Cundy, G Johnson, A McRobie
Proc. 14th Intern Conf IBPSA-Building Simulation, 2256-2263, 2015
LMPriors: Pre-Trained Language Models as Task-Specific Priors
K Choi, C Cundy, S Srivastava, S Ermon
First Workshop on Foundation Models for Decision Making, Neurips 2022, 2022
Predicting human deliberative judgments with machine learning
O Evans, A Stuhlmüller, C Cundy, R Carey, Z Kenton, T McGrath, ...
Technical report, Technical report, 2018
Flexible approximate inference via stratified normalizing flows
C Cundy, S Ermon
Conference on Uncertainty in Artificial Intelligence, 1288-1297, 2020
Exploring Hierarchy-Aware Inverse Reinforcement Learning
C Cundy, D Filan
First Workshop on Goal Specifications for Reinforcement Learning, ICML 2018 …, 2018
Privacy-constrained policies via mutual information regularized policy gradients
CJ Cundy, R Desai, S Ermon
International Conference on Artificial Intelligence and Statistics, 2809-2817, 2024
Sequencematch: Imitation learning for autoregressive sequence modelling with backtracking
C Cundy, S Ermon
arXiv preprint arXiv:2306.05426, 2023
Beyond Bayes-optimality: meta-learning what you know you don't know
J Grau-Moya, G Delétang, M Kunesch, T Genewein, E Catt, K Li, A Ruoss, ...
arXiv preprint arXiv:2209.15618, 2022
On the opportunities and challenges of foundation models for geoai (vision paper)
G Mai, W Huang, J Sun, S Song, D Mishra, N Liu, S Gao, T Liu, G Cong, ...
ACM Transactions on Spatial Algorithms and Systems, 2024
A Physics-Informed Machine Learning Approach for Predicting Atomized Drop Distributions in Liquid Jet Simulations
C Cundy, S Mirjalili, C Laurent, S Ermon, A Mani
Bulletin of the American Physical Society, 2023
Modeling secondary breakup in atomization processes via machine learning
C Cundy, S Mirjalili, S Ermon, A Mani
APS Division of Fluid Dynamics Meeting Abstracts, T01. 007, 2021
The system can't perform the operation now. Try again later.
Articles 1–18