On the broadcast of segmented messages in dynamic networks. - Sandipan Sikdar; Marcin Bodych; Rajib Ranjan Maiti; Biswajit Paria; Niloy Ganguly; Tyll Krueger; Animesh Mukherjee 001 (INFOCOM Workshops, 2015)

COMA-boost: co-operative multi agent AdaBoost. - Avisek Lahiri; Biswajit Paria; Prabir Kumar Biswas (ICVGIP, 2016)

A Neural Architecture Mimicking Humans End-to-End for Natural Language Inference. - Biswajit Paria; K. M. Annervaz; Ambedkar Dukkipati; Ankush Chatterjee; Sanjay Podder (CoRR, 2016)

Visualization Regularizers for Neural Network based Image Recognition. - Biswajit Paria; Anirban Santara; Pabitra Mitra (CoRR, 2016)

PolicyGAN: Training generative adversarial networks using policy gradient. - Biswajit Paria; Avisek Lahiri; Prabir Kumar Biswas (ICAPR, 2017)

Analytic Connectivity in General Hypergraphs. - Ashwin Guha; Muni Sreenivas Pydi; Biswajit Paria; Ambedkar Dukkipati (CoRR, 2017)

A Flexible Multi-Objective Bayesian Optimization Approach using Random Scalarizations. - Biswajit Paria; Kirthevasan Kandasamy; Barnabás Póczos (CoRR, 2018)

Forward Stagewise Additive Model for Collaborative Multiview Boosting. - Avisek Lahiri; Biswajit Paria; Prabir Kumar Biswas (IEEE Trans. Neural Networks Learn. Syst., 2018)

A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations. - Biswajit Paria; Kirthevasan Kandasamy; Barnabás Póczos (UAI, 2019)

Minimizing FLOPs to Learn Efficient Sparse Representations. - Biswajit Paria; Chih-Kuan Yeh; Ian En-Hsu Yen; Ning Xu; Pradeep Ravikumar; Barnabás Póczos (ICLR, 2020)

Autonomous discovery of battery electrolytes with robotic experimentation and machine-learning. - Adarsh Dave; Jared Mitchell; Kirthevasan Kandasamy; Sven Burke; Biswajit Paria; Barnabás Póczos; Jay Whitacre; Venkatasubramanian Viswanathan (CoRR, 2020)

Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly. - Kirthevasan Kandasamy; Karun Raju Vysyaraju; Willie Neiswanger; Biswajit Paria; Christopher R. Collins; Jeff Schneider 001; Barnabás Póczos; Eric P. Xing (J. Mach. Learn. Res., 2020)

Hierarchically Regularized Deep Forecasting. - Biswajit Paria; Rajat Sen; Amr Ahmed 001; Abhimanyu Das (CoRR, 2021)

Gradient-based Constrained Sampling from Language Models. - Sachin Kumar 009; Biswajit Paria; Yulia Tsvetkov (EMNLP, 2022)

An Experimental Design Perspective on Model-Based Reinforcement Learning. - Viraj Mehta; Biswajit Paria; Jeff Schneider 001; Stefano Ermon; Willie Neiswanger (ICLR, 2022)

A Top-Down Approach to Hierarchically Coherent Probabilistic Forecasting. - Abhimanyu Das; Weihao Kong; Biswajit Paria; Rajat Sen (CoRR, 2022)

Constrained Sampling from Language Models via Langevin Dynamics in Embedding Spaces. - Sachin Kumar 009; Biswajit Paria; Yulia Tsvetkov (CoRR, 2022)

Strategies for Black-Box and Multi-Objective Optimization - Biswajit Paria (2022)

Dirichlet Proportions Model for Hierarchically Coherent Probabilistic Forecasting. - Abhimanyu Das; Weihao Kong; Biswajit Paria; Rajat Sen (UAI, 2023)