Sehanobish, Arijit

13 publications

NeurIPS 2025 EUGens: Efficient, Unified and General Dense Layers Sang Min Kim, Byeongchan Kim, Arijit Sehanobish, Somnath Basu Roy Chowdhury, Rahul Kidambi, Dongseok Shim, Kumar Avinava Dubey, Snigdha Chaturvedi, Min-hwan Oh, Krzysztof Marcin Choromanski

AISTATS 2025 Optimal Time Complexity Algorithms for Computing General Random Walk Graph Kernels on Sparse Graphs Krzysztof Marcin Choromanski, Isaac Reid, Arijit Sehanobish, Kumar Avinava Dubey

ICLR 2025 Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning Somnath Basu Roy Chowdhury, Krzysztof Marcin Choromanski, Arijit Sehanobish, Kumar Avinava Dubey, Snigdha Chaturvedi

NeurIPS 2024 Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers Krzysztof Choromanski, Arijit Sehanobish, Somnath Basu Roy Chowdhury, Han Lin, Avinava Dubey, Tamas Sarlos, Snigdha Chaturvedi

ICLR 2024 Scalable Neural Network Kernels Arijit Sehanobish, Krzysztof Marcin Choromanski, Yunfan Zhao, Kumar Avinava Dubey, Valerii Likhosherstov

NeurIPS 2024 Structured Unrestricted-Rank Matrices for Parameter Efficient Finetuning Arijit Sehanobish, Avinava Dubey, Krzysztof Choromanski, Somnath Basu Roy Chowdhury, Deepali Jain, Vikas Sindhwani, Snigdha Chaturvedi

NeurIPSW 2024 Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning Somnath Basu Roy Chowdhury, Krzysztof Marcin Choromanski, Arijit Sehanobish, Kumar Avinava Dubey, Snigdha Chaturvedi

ICML 2023 Efficient Graph Field Integrators Meet Point Clouds Krzysztof Marcin Choromanski, Arijit Sehanobish, Han Lin, Yunfan Zhao, Eli Berger, Tetiana Parshakova, Alvin Pan, David Watkins, Tianyi Zhang, Valerii Likhosherstov, Somnath Basu Roy Chowdhury, Kumar Avinava Dubey, Deepali Jain, Tamas Sarlos, Snigdha Chaturvedi, Adrian Weller

ICML 2022 From Block-Toeplitz Matrices to Differential Equations on Graphs: Towards a General Theory for Scalable Masked Transformers Krzysztof Choromanski, Han Lin, Haoxian Chen, Tianyi Zhang, Arijit Sehanobish, Valerii Likhosherstov, Jack Parker-Holder, Tamas Sarlos, Adrian Weller, Thomas Weingarten

ICLR 2022 Hybrid Random Features Krzysztof Marcin Choromanski, Han Lin, Haoxian Chen, Arijit Sehanobish, Yuanzhe Ma, Deepali Jain, Jake Varley, Andy Zeng, Michael S Ryoo, Valerii Likhosherstov, Dmitry Kalashnikov, Vikas Sindhwani, Adrian Weller

AAAI 2021 Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using Self-Supervised Edge Features and Graph Neural Networks Arijit Sehanobish, Neal G. Ravindra, David van Dijk

NeurIPSW 2020 Permutation Invariant Networks to Learn Wasserstein Metrics Arijit Sehanobish, Neal G Ravindra, David van Dijk

AAAI 2020 Using Chinese Glyphs for Named Entity Recognition (Student Abstract) Chan Hee Song, Arijit Sehanobish