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ORCIDRupesh Kumar Srivastava
Person information
- affiliation: University of Lugano, Dalle Molle Institute for Artificial Intelligence Research (IDSIA)
- affiliation: Indian Institute of Technology Kanpur, Department of Mechanical Engineering
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2020 – today
- 2023
[i20]Nihat Engin Toklu, Timothy Atkinson, Vojtech Micka, Pawel Liskowski, Rupesh Kumar Srivastava:
EvoTorch: Scalable Evolutionary Computation in Python. CoRR abs/2302.12600 (2023)- [i19]Saeed Saremi, Rupesh Kumar Srivastava, Francis R. Bach:
Universal Smoothed Score Functions for Generative Modeling. CoRR abs/2303.11669 (2023) - [i18]Alex Graves, Rupesh Kumar Srivastava, Timothy Atkinson, Faustino J. Gomez:
Bayesian Flow Networks. CoRR abs/2308.07037 (2023) - 2022
- [c16]Miroslav Strupl, Francesco Faccio, Dylan R. Ashley, Rupesh Kumar Srivastava, Jürgen Schmidhuber:
Reward-Weighted Regression Converges to a Global Optimum. AAAI 2022: 8361-8369 - [c15]Saeed Saremi, Rupesh Kumar Srivastava:
Multimeasurement Generative Models. ICLR 2022 - [i17]Kai Arulkumaran, Dylan R. Ashley, Jürgen Schmidhuber, Rupesh Kumar Srivastava:
All You Need Is Supervised Learning: From Imitation Learning to Meta-RL With Upside Down RL. CoRR abs/2202.11960 (2022) - [i16]Dylan R. Ashley, Kai Arulkumaran, Jürgen Schmidhuber, Rupesh Kumar Srivastava:
Learning Relative Return Policies With Upside-Down Reinforcement Learning. CoRR abs/2202.12742 (2022) - [i15]Miroslav Strupl, Francesco Faccio, Dylan R. Ashley, Jürgen Schmidhuber, Rupesh Kumar Srivastava:
Upside-Down Reinforcement Learning Can Diverge in Stochastic Environments With Episodic Resets. CoRR abs/2205.06595 (2022) - 2021
- [i14]Miroslav Strupl, Francesco Faccio, Dylan R. Ashley
, Rupesh Kumar Srivastava, Jürgen Schmidhuber:
Reward-Weighted Regression Converges to a Global Optimum. CoRR abs/2107.09088 (2021) - [i13]Saeed Saremi, Rupesh Kumar Srivastava:
Multimeasurement Generative Models. CoRR abs/2112.09822 (2021) - 2020
- [c14]Nihat Engin Toklu, Pawel Liskowski, Rupesh Kumar Srivastava:
ClipUp: A Simple and Powerful Optimizer for Distribution-Based Policy Evolution. PPSN (2) 2020: 515-527 - [i12]Nihat Engin Toklu, Pawel Liskowski, Rupesh Kumar Srivastava:
ClipUp: A Simple and Powerful Optimizer for Distribution-based Policy Evolution. CoRR abs/2008.02387 (2020)
2010 – 2019
- 2019
- [i11]Lukasz Kidzinski, Carmichael F. Ong, Sharada Prasanna Mohanty, Jennifer L. Hicks, Sean F. Carroll, Bo Zhou, Hong-cheng Zeng, Fan Wang, Rongzhong Lian, Hao Tian, Wojciech Jaskowski, Garrett Andersen, Odd Rune Lykkebø, Nihat Engin Toklu, Pranav Shyam, Rupesh Kumar Srivastava, Sergey Kolesnikov, Oleksii Hrinchuk, Anton Pechenko, Mattias Ljungström, Zhen Wang, Xu Hu, Zehong Hu, Minghui Qiu, Jun Huang, Aleksei Shpilman, Ivan Sosin, Oleg Svidchenko, Aleksandra Malysheva, Daniel Kudenko, Lance Rane, Aditya Bhatt, Zhengfei Wang, Penghui Qi, Zeyang Yu, Peng Peng, Quan Yuan, Wenxin Li, Yunsheng Tian, Ruihan Yang, Pingchuan Ma, Shauharda Khadka, Somdeb Majumdar, Zach Dwiel, Yinyin Liu, Evren Tumer, Jeremy D. Watson, Marcel Salathé, Sergey Levine, Scott L. Delp:
Artificial Intelligence for Prosthetics - challenge solutions. CoRR abs/1902.02441 (2019) - [i10]Rupesh Kumar Srivastava, Pranav Shyam, Filipe Mutz, Wojciech Jaskowski, Jürgen Schmidhuber:
Training Agents using Upside-Down Reinforcement Learning. CoRR abs/1912.02877 (2019) - 2018
- [c13]Wonmin Byeon, Qin Wang, Rupesh Kumar Srivastava, Petros Koumoutsakos:
ContextVP: Fully Context-Aware Video Prediction. CVPR Workshops 2018: 1122-1126 - [c12]Wonmin Byeon, Qin Wang, Rupesh Kumar Srivastava, Petros Koumoutsakos:
ContextVP: Fully Context-Aware Video Prediction. ECCV (16) 2018: 781-797 - 2017
- [j1]Klaus Greff, Rupesh Kumar Srivastava, Jan Koutník, Bas R. Steunebrink, Jürgen Schmidhuber:
LSTM: A Search Space Odyssey. IEEE Trans. Neural Networks Learn. Syst. 28(10): 2222-2232 (2017) - [c11]Klaus Greff, Rupesh Kumar Srivastava, Jürgen Schmidhuber:
Highway and Residual Networks learn Unrolled Iterative Estimation. ICLR (Poster) 2017 - [c10]Julian Georg Zilly, Rupesh Kumar Srivastava, Jan Koutník, Jürgen Schmidhuber:
Recurrent Highway Networks. ICML 2017: 4189-4198 - [i9]Wonmin Byeon, Qin Wang, Rupesh Kumar Srivastava, Petros Koumoutsakos:
Fully Context-Aware Video Prediction. CoRR abs/1710.08518 (2017) - 2016
- [i8]Julian G. Zilly, Rupesh Kumar Srivastava, Jan Koutník, Jürgen Schmidhuber:
Recurrent Highway Networks. CoRR abs/1607.03474 (2016) - [i7]Klaus Greff, Rupesh Kumar Srivastava, Jürgen Schmidhuber:
Highway and Residual Networks learn Unrolled Iterative Estimation. CoRR abs/1612.07771 (2016) - 2015
- [c9]Hao Fang, Saurabh Gupta, Forrest N. Iandola, Rupesh Kumar Srivastava, Li Deng, Piotr Dollár, Jianfeng Gao, Xiaodong He, Margaret Mitchell, John C. Platt, C. Lawrence Zitnick, Geoffrey Zweig:
From captions to visual concepts and back. CVPR 2015: 1473-1482 - [c8]Rupesh Kumar Srivastava, Klaus Greff, Jürgen Schmidhuber:
Training Very Deep Networks. NIPS 2015: 2377-2385 - [c7]Rupesh Kumar Srivastava, Jonathan Masci, Faustino J. Gomez, Jürgen Schmidhuber:
Understanding Locally Competitive Networks. ICLR (Poster) 2015 - [i6]Klaus Greff, Rupesh Kumar Srivastava, Jan Koutník, Bas R. Steunebrink, Jürgen Schmidhuber:
LSTM: A Search Space Odyssey. CoRR abs/1503.04069 (2015) - [i5]Rupesh Kumar Srivastava, Klaus Greff, Jürgen Schmidhuber:
Highway Networks. CoRR abs/1505.00387 (2015) - [i4]Rupesh Kumar Srivastava, Klaus Greff, Jürgen Schmidhuber:
Training Very Deep Networks. CoRR abs/1507.06228 (2015) - [i3]Klaus Greff, Rupesh Kumar Srivastava, Jürgen Schmidhuber:
Binding via Reconstruction Clustering. CoRR abs/1511.06418 (2015) - 2014
- [i2]Hao Fang, Saurabh Gupta, Forrest N. Iandola, Rupesh Kumar Srivastava, Li Deng, Piotr Dollár, Jianfeng Gao, Xiaodong He, Margaret Mitchell, John C. Platt, C. Lawrence Zitnick, Geoffrey Zweig:
From Captions to Visual Concepts and Back. CoRR abs/1411.4952 (2014) - 2013
- [c6]Rupesh Kumar Srivastava, Jonathan Masci, Sohrob Kazerounian, Faustino J. Gomez, Jürgen Schmidhuber:
Compete to Compute. NIPS 2013: 2310-2318 - 2012
- [c5]Rupesh Kumar Srivastava, Jürgen Schmidhuber, Faustino J. Gomez:
Generalized compressed network search. GECCO (Companion) 2012: 647-648 - [c4]Rupesh Kumar Srivastava, Bas R. Steunebrink, Marijn F. Stollenga, Jürgen Schmidhuber:
Continually adding self-invented problems to the repertoire: First experiments with POWERPLAY. ICDL-EPIROB 2012: 1-6 - [c3]Rupesh Kumar Srivastava, Jürgen Schmidhuber, Faustino J. Gomez:
Generalized Compressed Network Search. PPSN (1) 2012: 337-346 - [i1]Rupesh Kumar Srivastava, Bas R. Steunebrink, Jürgen Schmidhuber:
First Experiments with PowerPlay. CoRR abs/1210.8385 (2012) - 2011
- [c2]Rupesh Kumar Srivastava, Kalyanmoy Deb:
An EA-based approach to design optimization using evidence theory. GECCO 2011: 1139-1146 - 2010
- [c1]Rupesh Kumar Srivastava, Kalyanmoy Deb:
Bayesian Reliability Analysis under Incomplete Information Using Evolutionary Algorithms. SEAL 2010: 435-444
Coauthor Index
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