Rupesh Kumar Srivastava

Publication Activity (10 Years)

Years Active: 2010-2023
Publications (10 Years): 22

Top Topics

Reinforcement Learning

Prune The Search Space

Eligibility Traces

Top Venues

IEEE Trans. Neural Networks Learn. Syst.

Publications

Saeed Saremi, Rupesh Kumar Srivastava, Francis Bach
Universal Smoothed Score Functions for Generative Modeling. CoRR (2023)
Nihat Engin Toklu, Timothy Atkinson, Vojtech Micka, Pawel Liskowski, Rupesh Kumar Srivastava
EvoTorch: Scalable Evolutionary Computation in Python. CoRR (2023)
Alex Graves, Rupesh Kumar Srivastava, Timothy Atkinson, Faustino J. Gomez
Bayesian Flow Networks. CoRR (2023)
Saeed Saremi, Rupesh Kumar Srivastava
Multimeasurement Generative Models. ICLR (2022)
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 (2022)
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 (2022)
Dylan R. Ashley, Kai Arulkumaran, Jürgen Schmidhuber, Rupesh Kumar Srivastava
Learning Relative Return Policies With Upside-Down Reinforcement Learning. CoRR (2022)
Miroslav Strupl, Francesco Faccio, Dylan R. Ashley, Rupesh Kumar Srivastava, Jürgen Schmidhuber
Reward-Weighted Regression Converges to a Global Optimum. AAAI (2022)
Saeed Saremi, Rupesh Kumar Srivastava
Multimeasurement Generative Models. CoRR (2021)
Miroslav Strupl, Francesco Faccio, Dylan R. Ashley, Rupesh Kumar Srivastava, Jürgen Schmidhuber
Reward-Weighted Regression Converges to a Global Optimum. CoRR (2021)
Nihat Engin Toklu, Pawel Liskowski, Rupesh Kumar Srivastava
ClipUp: A Simple and Powerful Optimizer for Distribution-Based Policy Evolution. PPSN (2) (2020)
Nihat Engin Toklu, Pawel Liskowski, Rupesh Kumar Srivastava
ClipUp: A Simple and Powerful Optimizer for Distribution-based Policy Evolution. CoRR (2020)
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 (2019)
Rupesh Kumar Srivastava, Pranav Shyam, Filipe Mutz, Wojciech Jaskowski, Jürgen Schmidhuber
Training Agents using Upside-Down Reinforcement Learning. CoRR (2019)
Wonmin Byeon, Qin Wang, Rupesh Kumar Srivastava, Petros Koumoutsakos
ContextVP: Fully Context-Aware Video Prediction. ECCV (16) (2018)
Wonmin Byeon, Qin Wang, Rupesh Kumar Srivastava, Petros Koumoutsakos
ContextVP: Fully Context-Aware Video Prediction. CVPR Workshops (2018)
Klaus Greff, Rupesh Kumar Srivastava, Jürgen Schmidhuber
Highway and Residual Networks learn Unrolled Iterative Estimation. ICLR (Poster) (2017)
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) (2017)
Julian Georg Zilly, Rupesh Kumar Srivastava, Jan Koutník, Jürgen Schmidhuber
Recurrent Highway Networks. ICML (2017)
Wonmin Byeon, Qin Wang, Rupesh Kumar Srivastava, Petros Koumoutsakos
Fully Context-Aware Video Prediction. CoRR (2017)
Julian G. Zilly, Rupesh Kumar Srivastava, Jan Koutník, Jürgen Schmidhuber
Recurrent Highway Networks. CoRR (2016)
Klaus Greff, Rupesh Kumar Srivastava, Jürgen Schmidhuber
Highway and Residual Networks learn Unrolled Iterative Estimation. CoRR (2016)
Klaus Greff, Rupesh Kumar Srivastava, Jan Koutník, Bas R. Steunebrink, Jürgen Schmidhuber
LSTM: A Search Space Odyssey. CoRR (2015)
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)
Rupesh Kumar Srivastava, Jonathan Masci, Faustino J. Gomez, Jürgen Schmidhuber
Understanding Locally Competitive Networks. ICLR (Poster) (2015)
Rupesh Kumar Srivastava, Klaus Greff, Jürgen Schmidhuber
Highway Networks. CoRR (2015)
Rupesh Kumar Srivastava, Klaus Greff, Jürgen Schmidhuber
Training Very Deep Networks. CoRR (2015)
Klaus Greff, Rupesh Kumar Srivastava, Jürgen Schmidhuber
Binding via Reconstruction Clustering. CoRR (2015)
Rupesh Kumar Srivastava, Klaus Greff, Jürgen Schmidhuber
Training Very Deep Networks. NIPS (2015)
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 (2014)
Rupesh Kumar Srivastava, Jonathan Masci, Sohrob Kazerounian, Faustino J. Gomez, Jürgen Schmidhuber
Compete to Compute. NIPS (2013)
Rupesh Kumar Srivastava, Jürgen Schmidhuber, Faustino J. Gomez
Generalized Compressed Network Search. PPSN (1) (2012)
Rupesh Kumar Srivastava, Jürgen Schmidhuber, Faustino J. Gomez
Generalized compressed network search. GECCO (Companion) (2012)
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)
Rupesh Kumar Srivastava, Bas R. Steunebrink, Jürgen Schmidhuber
First Experiments with PowerPlay CoRR (2012)
Rupesh Kumar Srivastava, Kalyanmoy Deb
An EA-based approach to design optimization using evidence theory. GECCO (2011)
Rupesh Kumar Srivastava, Kalyanmoy Deb
Bayesian Reliability Analysis under Incomplete Information Using Evolutionary Algorithms. SEAL (2010)