Filer Response Time Prediction Using Adaptively-Learned Forecasting Models Based on Counter Time Series Data. - Saurabh Deshpande; Kumar Dheenadayalan; G. Srinivasaraghavan 001; V. N. Muralidhara (ICMLA, 2016)

AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types. - Xin Luna Dong; Xiang He 007; Andrey Kan; Xian Li; Yan Liang 004; Jun Ma 029; Yifan Ethan Xu; Chenwei Zhang; Tong Zhao 002; Gabriel Blanco Saldana; Saurabh Deshpande; Alexandre Michetti Manduca; et al. (KDD, 2020)

FEM-based Real-Time Simulations of Large Deformations with Probabilistic Deep Learning. - Saurabh Deshpande; Jakub Lengiewicz; Stéphane P. A. Bordas (CoRR, 2021)

Convolution, aggregation and attention based deep neural networks for accelerating simulations in mechanics. - Saurabh Deshpande; Raúl I. Sosa; Stéphane P. A. Bordas; Jakub Lengiewicz (CoRR, 2022)

Data Driven Surrogate Frameworks for Computational Mechanics: Bayesian and Geometric Deep Learning Approaches. - Saurabh Deshpande (2023)

Graph Representation Learning Strategies for Omics Data: A Case Study on Parkinson's Disease. - Elisa Gómez de Lope; Saurabh Deshpande; Ramón Viñas Torné 001; Pietro Liò; Enrico Glaab; Stéphane P. A. Bordas (CoRR, 2024)

Gaussian process regression + deep neural network autoencoder for probabilistic surrogate modeling in nonlinear mechanics of solids. - Saurabh Deshpande; Hussein Rappel; Mark Hobbs; Stéphane P. A. Bordas; Jakub Lengiewicz (CoRR, 2024)

MAgNET: A graph U-Net architecture for mesh-based simulations. - Saurabh Deshpande; Stéphane P. A. Bordas; Jakub Lengiewicz (Eng. Appl. Artif. Intell., 2024)

REVEAL: Multi-turn Evaluation of Image-Input Harms for Vision LLM. - Madhur Jindal; Saurabh Deshpande (CoRR, 2025)

Advances and applications in inverse reinforcement learning: a comprehensive review. - Saurabh Deshpande; Rahee Walambe; Ketan Kotecha; Ganeshsree Selvachandran; Ajith Abraham (Neural Comput. Appl., 2025)