An improved fuzzy clustering method using modified Fukuyama-Sugeno cluster validity index. - Sailik Sengupta; Soham De; Amit Konar; Ramadoss Janarthanan (ReTIS, 2011)

Plagiarism Detection in Polyphonic Music using Monaural Signal Separation. - Soham De; Indradyumna Roy; Tarunima Prabhakar; Kriti Suneja; Sourish Chaudhuri; Rita Singh; Bhiksha Raj (INTERSPEECH, 2012)

Layer-Specific Adaptive Learning Rates for Deep Networks. - Bharat Singh; Soham De; Yangmuzi Zhang; Thomas A. Goldstein; Gavin Taylor (ICMLA, 2015)

Variance Reduction for Distributed Stochastic Gradient Descent. - Soham De; Gavin Taylor; Tom Goldstein (CoRR, 2015)

Scaling Up Distributed Stochastic Gradient Descent Using Variance Reduction. - Soham De; Gavin Taylor; Tom Goldstein (CoRR, 2015)

resMBS: Constructing a Financial Supply Chain from Prospectus. - Douglas Burdick; Soham De; Louiqa Raschid; Mingchao Shao; Zheng Xu 002; Elena Zotkina (DSMM@SIGMOD, 2016)

Efficient Distributed SGD with Variance Reduction. - Soham De; Tom Goldstein (ICDM, 2016)

An Empirical Study of ADMM for Nonconvex Problems. - Zheng Xu 002; Soham De; Mário A. T. Figueiredo; Christoph Studer; Tom Goldstein (CoRR, 2016)

Using Game Theory to Study the Evolution of Cultural Norms. - Soham De; Dana S. Nau; Michele Gelfand (CoRR, 2016)

Big Batch SGD: Automated Inference using Adaptive Batch Sizes. - Soham De; Abhay Kumar Yadav; David W. Jacobs; Tom Goldstein (CoRR, 2016)

Automated Inference with Adaptive Batches. - Soham De; Abhay Kumar Yadav; David W. Jacobs; Tom Goldstein (AISTATS, 2017)

Understanding Norm Change: An Evolutionary Game-Theoretic Approach. - Soham De; Dana S. Nau; Michele J. Gelfand (AAMAS, 2017)

Son of Zorn's lemma: Targeted style transfer using instance-aware semantic segmentation. - Carlos Domingo Castillo; Soham De; Xintong Han; Bharat Singh; Abhay Kumar Yadav; Tom Goldstein (ICASSP, 2017)

Training Quantized Nets: A Deeper Understanding. - Hao Li 022; Soham De; Zheng Xu 002; Christoph Studer; Hanan Samet; Tom Goldstein (NIPS, 2017)

Understanding Norm Change: An Evolutionary Game-Theoretic Approach (Extended Version). - Soham De; Dana S. Nau; Michele J. Gelfand (CoRR, 2017)

Tipping Points for Norm Change in Human Cultures. - Soham De; Dana S. Nau; Xinyue Pan; Michele J. Gelfand (SBP-BRiMS, 2018)

Convergence guarantees for RMSProp and ADAM in non-convex optimization and their comparison to Nesterov acceleration on autoencoders. - Amitabh Basu; Soham De; Anirbit Mukherjee; Enayat Ullah (CoRR, 2018)

Fast optimization methods for machine learning, and game-theoretic models of cultural evolution. - Soham De (2018)

Adversarial Robustness through Local Linearization. - Chongli Qin; James Martens; Sven Gowal; Dilip Krishnan; Krishnamurthy Dvijotham; Alhussein Fawzi; Soham De; Robert Stanforth; Pushmeet Kohli (NeurIPS, 2019)

Efficient Neural Network Verification with Exactness Characterization. - Krishnamurthy (Dj) Dvijotham; Robert Stanforth; Sven Gowal; Chongli Qin; Soham De; Pushmeet Kohli (UAI, 2019)

The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent. - Karthik Abinav Sankararaman; Soham De; Zheng Xu 002; W. Ronny Huang; Tom Goldstein (ICML, 2020)

On the Generalization Benefit of Noise in Stochastic Gradient Descent. - Samuel L. Smith; Erich Elsen; Soham De (ICML, 2020)

Batch Normalization Biases Residual Blocks Towards the Identity Function in Deep Networks. - Soham De; Samuel L. Smith (NeurIPS, 2020)

Modeling Citation Trajectories of Scientific Papers. - Dattatreya Mohapatra; Siddharth Pal; Soham De; Ponnurangam Kumaraguru; Tanmoy Chakraborty 002 (PAKDD (2), 2020)

Batch Normalization Biases Deep Residual Networks Towards Shallow Paths. - Soham De; Samuel L. Smith (CoRR, 2020)

BYOL works even without batch statistics. - Pierre H. Richemond; Jean-Bastien Grill; Florent Altché; Corentin Tallec; Florian Strub; Andrew Brock; Samuel L. Smith; Soham De; Razvan Pascanu; Bilal Piot; Michal Valko (CoRR, 2020)

Characterizing signal propagation to close the performance gap in unnormalized ResNets. - Andrew Brock; Soham De; Samuel L. Smith (ICLR, 2021)

On the Origin of Implicit Regularization in Stochastic Gradient Descent. - Samuel L. Smith; Benoit Dherin; David G. T. Barrett; Soham De (ICLR, 2021)

High-Performance Large-Scale Image Recognition Without Normalization. - Andy Brock; Soham De; Samuel L. Smith; Karen Simonyan (ICML, 2021)

Drawing Multiple Augmentation Samples Per Image During Training Efficiently Decreases Test Error. - Stanislav Fort; Andrew Brock; Razvan Pascanu; Soham De; Samuel L. Smith (CoRR, 2021)

A study on the plasticity of neural networks. - Tudor Berariu; Wojciech Czarnecki 001; Soham De; Jörg Bornschein; Samuel L. Smith; Razvan Pascanu; Claudia Clopath (CoRR, 2021)

Note: Picking Sides: The influencer-driven #HijabBan discourse on Twitter. - Soham De; Anmol Panda; Joyojeet Pal (COMPASS, 2022)

Closed Ranks: The Discursive Value of Military Support for Indian Politicians on Social Media. - Agrima Seth; Soham De; Arshia Arya; Steven Wilkinson; Sushant Singh; Joyojeet Pal (ICTD, 2022)

DISMISS: Database of Indian Social Media Influencers on Twitter. - Arshia Arya; Soham De; Dibyendu Mishra; Gazal Shekhawat; Ankur Sharma; Anmol Panda; Faisal M. Lalani; Parantak Singh; Ramaravind Kommiya Mothilal; Rynaa Grover; Sachita Nishal; Saloni Dash; et al. (ICWSM, 2022)

Regularising for invariance to data augmentation improves supervised learning. - Aleksander Botev; Matthias Bauer 001; Soham De (CoRR, 2022)

Database of Indian Social Media Influencers on Twitter. - Arshia Arya; Soham De; Dibyendu Mishra; Gazal Shekhawat; Ankur Sharma; Anmol Panda; Faisal M. Lalani; Parantak Singh; Ramaravind Kommiya Mothilal; Rynaa Grover; Sachita Nishal; Saloni Dash; et al. (CoRR, 2022)

Unlocking High-Accuracy Differentially Private Image Classification through Scale. - Soham De; Leonard Berrada; Jamie Hayes; Samuel L. Smith; Borja Balle (CoRR, 2022)

Resurrecting Recurrent Neural Networks for Long Sequences. - Antonio Orvieto; Samuel L. Smith; Albert Gu; Anushan Fernando; Çaglar Gülçehre; Razvan Pascanu; Soham De (ICML, 2023)

Differentially Private Diffusion Models Generate Useful Synthetic Images. - Sahra Ghalebikesabi; Leonard Berrada; Sven Gowal; Ira Ktena; Robert Stanforth; Jamie Hayes; Soham De; Samuel L. Smith; Olivia Wiles; Borja Balle (CoRR, 2023)

On the Universality of Linear Recurrences Followed by Nonlinear Projections. - Antonio Orvieto; Soham De; Çaglar Gülçehre; Razvan Pascanu; Samuel L. Smith (CoRR, 2023)

Unlocking Accuracy and Fairness in Differentially Private Image Classification. - Leonard Berrada; Soham De; Judy Hanwen Shen; Jamie Hayes; Robert Stanforth; David Stutz; Pushmeet Kohli; Samuel L. Smith; Borja Balle (CoRR, 2023)

ConvNets Match Vision Transformers at Scale. - Samuel L. Smith; Andrew Brock; Leonard Berrada; Soham De (CoRR, 2023)

Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues. - Antonio Orvieto; Soham De; Caglar Gulcehre; Razvan Pascanu; Samuel L. Smith (ICML, 2024)

On the Influence and Political Leaning of Overlap between Propaganda Communities. - Anirban Sen; Soumyasis Gun; Soham De; Joyojeet Pal (ACM J. Comput. Sustain. Soc., 2024)

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models. - Soham De; Samuel L. Smith; Anushan Fernando; Aleksandar Botev; George-Cristian Muraru; Albert Gu; Ruba Haroun; Leonard Berrada; Yutian Chen 001; Srivatsan Srinivasan; Guillaume Desjardins; Arnaud Doucet; et al. (CoRR, 2024)

RecurrentGemma: Moving Past Transformers for Efficient Open Language Models. - Aleksandar Botev; Soham De; Samuel L. Smith; Anushan Fernando; George-Cristian Muraru; Ruba Haroun; Leonard Berrada; Razvan Pascanu; Pier Giuseppe Sessa; Robert Dadashi; Léonard Hussenot; Johan Ferret; et al. (CoRR, 2024)

Networks and Influencers in Online Propaganda Events: A Comparative Study of Three Cases in India. - Anirban Sen; Soham De; Joyojeet Pal (Proc. ACM Hum. Comput. Interact., 2024)

Supernotes: Driving Consensus in Crowd-Sourced Fact-Checking. - Soham De; Michiel A. Bakker; Jay Baxter; Martin Saveski (WWW, 2025)

How do language models learn facts? Dynamics, curricula and hallucinations. - Nicolas Zucchet; Jörg Bornschein; Stephanie C. Y. Chan; Andrew K. Lampinen; Razvan Pascanu; Soham De (CoRR, 2025)

From job titles to jawlines: Using context voids to study generative AI systems. - Shahan Ali Memon; Soham De; Sungha Kang; Riyan Mujtaba; Bedoor K. AlShebli; Katie Davis 001; Jaime Snyder; Jevin D. West (CoRR, 2025)

Scaling Human Judgment in Community Notes with LLMs. - Haiwen Li; Soham De; Manon Revel; Andreas Haupt; Brad Miller 003; Keith Coleman; Jay Baxter; Martin Saveski; Michiel A. Bakker (CoRR, 2025)

Optimizers Qualitatively Alter Solutions And We Should Leverage This. - Razvan Pascanu; Clare Lyle; Ionut-Vlad Modoranu; Naima Elosegui Borras; Dan Alistarh; Petar Velickovic; Sarath Chandar; Soham De; James Martens (CoRR, 2025)