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Evan Racah
Evan Racah
MosaicML
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Title
Cited by
Cited by
Year
Application of deep convolutional neural networks for detecting extreme weather in climate datasets
Y Liu, E Racah, J Correa, A Khosrowshahi, D Lavers, K Kunkel, ...
arXiv preprint arXiv:1605.01156, 2016
3822016
Unsupervised state representation learning in atari
A Anand*, E Racah*, S Ozair*, Y Bengio, MA Côté, RD Hjelm
NeurIPS 2019, 2019
2622019
ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events
E Racah, C Beckham, T Maharaj, SE Kahou, M Prabhat, C Pal
NeurIPS 2017, 2017
2602017
Deep learning at 15pf: supervised and semi-supervised classification for scientific data
T Kurth, J Zhang, N Satish, E Racah, I Mitliagkas, MMA Patwary, T Malas, ...
Proceedings of the International Conference for High Performance Computing …, 2017
952017
Matrix factorizations at scale: A comparison of scientific data analytics in Spark and C+ MPI using three case studies
A Gittens, A Devarakonda, E Racah, M Ringenburg, L Gerhardt, ...
2016 IEEE International Conference on Big Data (Big Data), 204-213, 2016
852016
H5spark: bridging the i/o gap between spark and scientific data formats on hpc systems
J Liu, E Racah, Q Koziol, RS Canon, A Gittens, L Gerhardt, S Byna, ...
Cray user group, 2016
57*2016
Deep Neural Networks for Physics Analysis on low-level whole-detector data at the LHC
W Bhimji, SA Farrell, T Kurth, M Paganini, E Racah
Journal of Physics: Conference Series, 2017
552017
Panda: Extreme scale parallel k-nearest neighbor on distributed architectures
MMA Patwary, NR Satish, N Sundaram, J Liu, P Sadowski, E Racah, ...
2016 IEEE international parallel and distributed processing symposium (IPDPS …, 2016
442016
Revealing fundamental physics from the daya bay neutrino experiment using deep neural networks
E Racah, S Ko, P Sadowski, W Bhimji, C Tull, SY Oh, P Baldi
2016 15th IEEE International Conference on Machine Learning and Applications …, 2016
392016
Hierarchical model-based imitation learning for planning in autonomous driving
E Bronstein, M Palatucci, D Notz, B White, A Kuefler, Y Lu, S Paul, ...
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022
352022
The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement Learning
H van Seijen, H Nekoei, E Racah, S Chandar
Advances in Neural Information Processing Systems, 2020
142020
A multi-platform evaluation of the randomized CX low-rank matrix factorization in Spark
A Gittens, J Kottalam, J Yang, MF Ringenburg, J Chhugani, E Racah, ...
2016 IEEE International Parallel and Distributed Processing Symposium …, 2016
92016
Slot Contrastive Networks: A Contrastive Approach for Representing Objects
E Racah, S Chandar
ICML 2020 Workshop on Object-Oriented Learning, 2020
82020
Deep learning for detecting extreme weather patterns
M Mudigonda, P Ram, K Kashinath, E Racah, A Mahesh, Y Liu, ...
Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote …, 2021
52021
Toward interactive supercomputing at NERSC with Jupyter
R Thomas, S Canon, S Cholia, L Gerhardt, E Racah
Cray User Group (CUG) Conference Proceedings, 2017
52017
Automated detection of fronts using a deep learning algorithm
KE Kunkel, JC Biard, E Racah
98th American Meteorological Society Annual Meeting, 2018
32018
Supervise Thyself: Examining Self-Supervised Representations in Interactive Environments
E Racah, C Pal
ICML Workshop on Self-Supervised Learning 2019, 2019
12019
Characterizing the Performance of Analytics Workloads on the Cray XC40
M Ringenburg, S Zhang, K Maschhoff, B Sparks, E Racah
Cray User Group (CUG) meeting 5, 2016
12016
Unsupervised representation learning in interactive environments
E Racah
Master's Thesis, UdeM, 2020
2020
Matrix Factorizations at Scale: a Comparison of Scientific Data Analytics in Spark and C+ MPI
A Gittens, A Devarakonda, E Racah
2016
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Articles 1–20