Bayesian Reliability Analysis under Incomplete Information Using Evolutionary Algorithms. - Rupesh Kumar Srivastava; Kalyanmoy Deb (SEAL, 2010)

An EA-based approach to design optimization using evidence theory. - Rupesh Kumar Srivastava; Kalyanmoy Deb (GECCO, 2011)

Continually adding self-invented problems to the repertoire: First experiments with POWERPLAY. - Rupesh Kumar Srivastava; Bas R. Steunebrink; Marijn F. Stollenga; Jürgen Schmidhuber (ICDL-EPIROB, 2012)

Generalized Compressed Network Search. - Rupesh Kumar Srivastava; Jürgen Schmidhuber; Faustino J. Gomez (PPSN (1), 2012)

First Experiments with PowerPlay - Rupesh Kumar Srivastava; Bas R. Steunebrink; Jürgen Schmidhuber (CoRR, 2012)

Compete to Compute. - Rupesh Kumar Srivastava; Jonathan Masci; Sohrob Kazerounian; Faustino J. Gomez; Jürgen Schmidhuber (NIPS, 2013)

From captions to visual concepts and back. - Hao Fang 002; Saurabh Gupta 001; Forrest N. Iandola; Rupesh Kumar Srivastava; Li Deng 001; Piotr Dollár; Jianfeng Gao 001; Xiaodong He 001; Margaret Mitchell; John C. Platt; C. Lawrence Zitnick; Geoffrey Zweig (CVPR, 2015)

Training Very Deep Networks. - Rupesh Kumar Srivastava; Klaus Greff; Jürgen Schmidhuber (NIPS, 2015)

Binding via Reconstruction Clustering. - Klaus Greff; Rupesh Kumar Srivastava; Jürgen Schmidhuber (CoRR, 2015)

Highway Networks. - Rupesh Kumar Srivastava; Klaus Greff; Jürgen Schmidhuber (CoRR, 2015)

Understanding Locally Competitive Networks. - Rupesh Kumar Srivastava; Jonathan Masci; Faustino J. Gomez; Jürgen Schmidhuber (ICLR (Poster), 2015)

Highway and Residual Networks learn Unrolled Iterative Estimation. - Klaus Greff; Rupesh Kumar Srivastava; Jürgen Schmidhuber (ICLR (Poster), 2017)

Recurrent Highway Networks. - Julian Georg Zilly; Rupesh Kumar Srivastava; Jan Koutník; Jürgen Schmidhuber (ICML, 2017)

Fully Context-Aware Video Prediction. - Wonmin Byeon; Qin Wang 013; Rupesh Kumar Srivastava; Petros Koumoutsakos (CoRR, 2017)

LSTM: A Search Space Odyssey. - Klaus Greff; Rupesh Kumar Srivastava; Jan Koutník; Bas R. Steunebrink; Jürgen Schmidhuber (IEEE Trans. Neural Networks Learn. Syst., 2017)

ContextVP: Fully Context-Aware Video Prediction. - Wonmin Byeon; Qin Wang 013; Rupesh Kumar Srivastava; Petros Koumoutsakos (CVPR Workshops, 2018)

Artificial Intelligence for Prosthetics - challenge solutions. - Lukasz Kidzinski; Carmichael F. Ong; Sharada Prasanna Mohanty; Jennifer L. Hicks; Sean F. Carroll; Bo Zhou; Hong-cheng Zeng; Fan Wang 021; Rongzhong Lian; Hao Tian 005; Wojciech Jaskowski; Garrett Andersen; et al. (CoRR, 2019)

Training Agents using Upside-Down Reinforcement Learning. - Rupesh Kumar Srivastava; Pranav Shyam; Filipe Mutz; Wojciech Jaskowski; Jürgen Schmidhuber (CoRR, 2019)

ClipUp: A Simple and Powerful Optimizer for Distribution-Based Policy Evolution. - Nihat Engin Toklu; Pawel Liskowski; Rupesh Kumar Srivastava (PPSN (2), 2020)

Reward-Weighted Regression Converges to a Global Optimum. - Miroslav Strupl; Francesco Faccio; Dylan R. Ashley; Rupesh Kumar Srivastava; Jürgen Schmidhuber (AAAI, 2022)

Multimeasurement Generative Models. - Saeed Saremi; Rupesh Kumar Srivastava (ICLR, 2022)

All You Need Is Supervised Learning: From Imitation Learning to Meta-RL With Upside Down RL. - Kai Arulkumaran; Dylan R. Ashley; Jürgen Schmidhuber; Rupesh Kumar Srivastava (CoRR, 2022)

Learning Relative Return Policies With Upside-Down Reinforcement Learning. - Dylan R. Ashley; Kai Arulkumaran; Jürgen Schmidhuber; Rupesh Kumar Srivastava (CoRR, 2022)

Upside-Down Reinforcement Learning Can Diverge in Stochastic Environments With Episodic Resets. - Miroslav Strupl; Francesco Faccio; Dylan R. Ashley; Jürgen Schmidhuber; Rupesh Kumar Srivastava (CoRR, 2022)

EvoTorch: Scalable Evolutionary Computation in Python. - Nihat Engin Toklu; Timothy Atkinson 001; Vojtech Micka; Pawel Liskowski; Rupesh Kumar Srivastava (CoRR, 2023)

Universal Smoothed Score Functions for Generative Modeling. - Saeed Saremi; Rupesh Kumar Srivastava; Francis R. Bach (CoRR, 2023)

Bayesian Flow Networks. - Alex Graves; Rupesh Kumar Srivastava; Timothy Atkinson 001; Faustino J. Gomez (CoRR, 2023)

On the Convergence and Stability of Upside-Down Reinforcement Learning, Goal-Conditioned Supervised Learning, and Online Decision Transformers. - Miroslav Strupl; Oleg Szehr; Francesco Faccio; Dylan R. Ashley; Rupesh Kumar Srivastava; Jürgen Schmidhuber (CoRR, 2025)