Enriching textbooks through data mining. - Rakesh Agrawal 001; Sreenivas Gollapudi; Krishnaram Kenthapadi; Nitish Srivastava; Raja Velu (ACM DEV, 2010)

Improving neural networks by preventing co-adaptation of feature detectors - Geoffrey E. Hinton; Nitish Srivastava; Alex Krizhevsky; Ilya Sutskever; Ruslan Salakhutdinov (CoRR, 2012)

Discriminative Transfer Learning with Tree-based Priors. - Nitish Srivastava; Ruslan Salakhutdinov (NIPS, 2013)

Modeling Documents with Deep Boltzmann Machines. - Nitish Srivastava; Ruslan Salakhutdinov; Geoffrey E. Hinton (UAI, 2013)

Learning Generative Models with Visual Attention. - Yichuan Tang; Nitish Srivastava; Ruslan Salakhutdinov (NIPS, 2014)

Dropout: a simple way to prevent neural networks from overfitting. - Nitish Srivastava; Geoffrey E. Hinton; Alex Krizhevsky; Ilya Sutskever; Ruslan Salakhutdinov (J. Mach. Learn. Res., 2014)

Multimodal learning with deep Boltzmann machines. - Nitish Srivastava; Ruslan Salakhutdinov (J. Mach. Learn. Res., 2014)

Exploiting Image-trained CNN Architectures for Unconstrained Video Classification. - Shengxin Zha; Florian Luisier; Walter Andrews; Nitish Srivastava; Ruslan Salakhutdinov (BMVC, 2015)

Unsupervised Learning of Video Representations using LSTMs. - Nitish Srivastava; Elman Mansimov; Ruslan Salakhutdinov (ICML, 2015)

Initialization Strategies of Spatio-Temporal Convolutional Neural Networks. - Elman Mansimov; Nitish Srivastava; Ruslan Salakhutdinov (CoRR, 2015)

Deep Learning Models for Unsupervised and Transfer Learning. - Nitish Srivastava (2017)

Geometric Capsule Autoencoders for 3D Point Clouds. - Nitish Srivastava; Hanlin Goh; Ruslan Salakhutdinov (CoRR, 2019)

Capsules with Inverted Dot-Product Attention Routing. - Yao-Hung Hubert Tsai; Nitish Srivastava; Hanlin Goh; Ruslan Salakhutdinov (ICLR, 2020)

Unconstrained Scene Generation with Locally Conditioned Radiance Fields. - Terrance DeVries; Miguel Ángel Bautista 001; Nitish Srivastava; Graham W. Taylor; Joshua M. Susskind (ICCV, 2021)

Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning. - Yue Wu 001; Shuangfei Zhai; Nitish Srivastava; Joshua M. Susskind; Jian Zhang 050; Ruslan Salakhutdinov; Hanlin Goh (ICML, 2021)

On the generalization of learning-based 3D reconstruction. - Miguel Ángel Bautista 001; Walter Talbott; Shuangfei Zhai; Nitish Srivastava; Joshua M. Susskind (WACV, 2021)

An Attention Free Transformer. - Shuangfei Zhai; Walter Talbott; Nitish Srivastava; Chen Huang 001; Hanlin Goh; Ruixiang Zhang; Josh M. Susskind (CoRR, 2021)

Robust Robotic Control from Pixels using Contrastive Recurrent State-Space Models. - Nitish Srivastava; Walter Talbott; Martin Bertran Lopez; Shuangfei Zhai; Josh M. Susskind (CoRR, 2021)

Efficient Embedding of Semantic Similarity in Control Policies via Entangled Bisimulation. - Martin Bertran Lopez; Walter Talbott; Nitish Srivastava; Joshua M. Susskind (CoRR, 2022)

Vesper: A Versatile Sparse Linear Algebra Accelerator With Configurable Compute Patterns. - Hanchen Jin; Zichao Yue; Zhongyuan Zhao 004; Yixiao Du; Chenhui Deng; Nitish Srivastava; Zhiru Zhang (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2025)