Evan Racah - RankMe

21 papers A* 2A 3C 1Journal 12Unranked 3

Year	Rank	Type	Title / Venue / Authors
2022	A	`conf`	Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving. IROS Eli Bronstein, Mark Palatucci, Dominik Notz, Brandyn White, Alex Kuefler, Yiren Lu, Supratik Paul, Payam Nikdel, Paul Mougin, Hongge Chen, Justin Fu, Austin Abrams, Punit Shah, Evan Racah, Benjamin Frenkel, Shimon Whiteson, Dragomir Anguelov
2022	J	`jnl`	Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving. CoRR Eli Bronstein, Mark Palatucci, Dominik Notz, Brandyn White, Alex Kuefler, Yiren Lu, Supratik Paul, Payam Nikdel, Paul Mougin, Hongge Chen, Justin Fu, Austin Abrams, Punit Shah, Evan Racah, Benjamin Frenkel, Shimon Whiteson, Dragomir Anguelov
2020	J	`jnl`	Slot Contrastive Networks: A Contrastive Approach for Representing Objects. CoRR Evan Racah, Sarath Chandar
2020	A*	`conf`	The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement Learning. NeurIPS Harm van Seijen, Hadi Nekoei, Evan Racah, Sarath Chandar
2020	J	`jnl`	The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement Learning. CoRR Harm van Seijen, Hadi Nekoei, Evan Racah, Sarath Chandar
2019	J	`jnl`	Supervise Thyself: Examining Self-Supervised Representations in Interactive Environments. CoRR Evan Racah, Christopher J. Pal
2019	A*	`conf`	Unsupervised State Representation Learning in Atari. NeurIPS Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, Marc-Alexandre Côté, R. Devon Hjelm
2019	J	`jnl`	Unsupervised State Representation Learning in Atari. CoRR Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, Marc-Alexandre Côté, R. Devon Hjelm
2017	J	`jnl`	Deep Learning at 15PF: Supervised and Semi-Supervised Classification for Scientific Data. CoRR Thorsten Kurth, Jian Zhang, Nadathur Satish, Ioannis Mitliagkas, Evan Racah, Md. Mostofa Ali Patwary, Tareq M. Malas, Narayanan Sundaram, Wahid Bhimji, Mikhail Smorkalov, Jack Deslippe, Mikhail Shiryaev, Srinivas Sridharan, Prabhat, Pradeep Dubey
2017	J	`jnl`	Deep Neural Networks for Physics Analysis on low-level whole-detector data at the LHC. CoRR Wahid Bhimji, Steven Andrew Farrell, Thorsten Kurth, Michela Paganini, Prabhat, Evan Racah
2017	A	`conf`	Deep learning at 15PF: supervised and semi-supervised classification for scientific data. SC Thorsten Kurth, Jian Zhang, Nadathur Satish, Evan Racah, Ioannis Mitliagkas, Md. Mostofa Ali Patwary, Tareq M. Malas, Narayanan Sundaram, Wahid Bhimji, Mikhail Smorkalov, Jack Deslippe, Mikhail Shiryaev, Srinivas Sridharan, Prabhat, Pradeep Dubey
2017	—	`conf`	ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events. NIPS Evan Racah, Christopher Beckham, Tegan Maharaj, Samira Ebrahimi Kahou, Prabhat, Chris Pal
2016	—	`conf`	A Multi-Platform Evaluation of the Randomized CX Low-Rank Matrix Factorization in Spark. IPDPS Workshops Alex Gittens, Jey Kottalam, Jiyan Yang, Michael F. Ringenburg, Jatin Chhugani, Evan Racah, Mohitdeep Singh, Yushu Yao, Curt Fischer, Oliver Rübel, Benjamin P. Bowen, Norman G. Lewis, Michael W. Mahoney, Venkat Krishnamurthy, Prabhat
2016	J	`jnl`	Application of Deep Convolutional Neural Networks for Detecting Extreme Weather in Climate Datasets. CoRR Yunjie Liu, Evan Racah, Prabhat, Joaquin Correa, Amir Khosrowshahi, David Lavers, Kenneth Kunkel, Michael F. Wehner, William D. Collins
2016	J	`jnl`	Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies. CoRR Alex Gittens, Aditya Devarakonda, Evan Racah, Michael F. Ringenburg, Lisa Gerhardt, Jey Kottalam, Jialin Liu, Kristyn J. Maschhoff, Shane Canon, Jatin Chhugani, Pramod Sharma, Jiyan Yang, James Demmel, Jim Harrell, Venkat Krishnamurthy, Michael W. Mahoney, Prabhat
2016	—	`conf`	Matrix factorizations at scale: A comparison of scientific data analytics in spark and C+MPI using three case studies. IEEE BigData Alex Gittens, Aditya Devarakonda, Evan Racah, Michael F. Ringenburg, Lisa Gerhardt, Jey Kottalam, Jialin Liu, Kristyn J. Maschhoff, Shane Canon, Jatin Chhugani, Pramod Sharma, Jiyan Yang, James Demmel, Jim Harrell, Venkat Krishnamurthy, Michael W. Mahoney, Prabhat
2016	A	`conf`	PANDA: Extreme Scale Parallel K-Nearest Neighbor on Distributed Architectures. IPDPS Md. Mostofa Ali Patwary, Nadathur Rajagopalan Satish, Narayanan Sundaram, Jialin Liu, Peter J. Sadowski, Evan Racah, Surendra Byna, Craig Tull, Wahid Bhimji, Prabhat, Pradeep Dubey
2016	J	`jnl`	PANDA: Extreme Scale Parallel K-Nearest Neighbor on Distributed Architectures. CoRR Md. Mostofa Ali Patwary, Nadathur Rajagopalan Satish, Narayanan Sundaram, Jialin Liu, Peter J. Sadowski, Evan Racah, Surendra Byna, Craig Tull, Wahid Bhimji, Prabhat, Pradeep Dubey
2016	C	`conf`	Revealing Fundamental Physics from the Daya Bay Neutrino Experiment Using Deep Neural Networks. ICMLA Evan Racah, Seyoon Ko, Peter J. Sadowski, Wahid Bhimji, Craig Tull, Sang-Yun Oh, Pierre Baldi, Prabhat
2016	J	`jnl`	Revealing Fundamental Physics from the Daya Bay Neutrino Experiment using Deep Neural Networks. CoRR Evan Racah, Seyoon Ko, Peter J. Sadowski, Wahid Bhimji, Craig Tull, Sang-Yun Oh, Pierre Baldi, Prabhat
2016	J	`jnl`	Semi-Supervised Detection of Extreme Weather Events in Large Climate Datasets. CoRR Evan Racah, Christopher Beckham, Tegan Maharaj, Prabhat, Christopher J. Pal