SL - FII: Syntactic and Lexical Constraints with Frequency based Iterative Improvement for Disease Mention Recognition in News Headlines. - Sidak Pal Singh; Sopan Khosla; Sajal Rustagi; Manisha Patel; Dhaval Patel 002 (BAI@IJCAI, 2016)

RaaS and Hierarchical Aggregation Revisited. - Rohit Ranchal; Sidak Pal Singh; Pelin Angin; Ajay Mohindra; Hui Lei 001; Bharat K. Bhargava (ICWS, 2017)

Wasserstein is all you need. - Sidak Pal Singh; Andreas Hug; Aymeric Dieuleveut; Martin Jaggi (CoRR, 2018)

GLOSS: Generative Latent Optimization of Sentence Representations. - Sidak Pal Singh; Angela Fan; Michael Auli (CoRR, 2019)

Context Mover's Distance & Barycenters: Optimal Transport of Contexts for Building Representations. - Sidak Pal Singh; Andreas Hug; Aymeric Dieuleveut; Martin Jaggi (AISTATS, 2020)

WoodFisher: Efficient Second-Order Approximation for Neural Network Compression. - Sidak Pal Singh; Dan Alistarh (NeurIPS, 2020)

Model Fusion via Optimal Transport. - Sidak Pal Singh; Martin Jaggi (NeurIPS, 2020)

WoodFisher: Efficient second-order approximations for model compression. - Sidak Pal Singh; Dan Alistarh (CoRR, 2020)

Analytic Insights into Structure and Rank of Neural Network Hessian Maps. - Sidak Pal Singh; Gregor Bachmann; Thomas Hofmann (NeurIPS, 2021)

Phenomenology of Double Descent in Finite-Width Neural Networks. - Sidak Pal Singh; Aurélien Lucchi; Thomas Hofmann; Bernhard Schölkopf (ICLR, 2022)

Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse. - Lorenzo Noci; Sotiris Anagnostidis; Luca Biggio; Antonio Orvieto; Sidak Pal Singh; Aurélien Lucchi (NeurIPS, 2022)

The Hessian perspective into the Nature of Convolutional Neural Networks. - Sidak Pal Singh; Thomas Hofmann; Bernhard Schölkopf (ICML, 2023)

Some Fundamental Aspects about Lipschitz Continuity of Neural Network Functions. - Grigory Khromov; Sidak Pal Singh (CoRR, 2023)

On the curvature of the loss landscape. - Alison Pouplin; Hrittik Roy; Sidak Pal Singh; Georgios Arvanitidis (CoRR, 2023)

Towards guarantees for parameter isolation in continual learning. - Giulia Lanzillotta; Sidak Pal Singh; Benjamin F. Grewe; Thomas Hofmann (CoRR, 2023)

Rethinking Attention: Exploring Shallow Feed-Forward Neural Networks as an Alternative to Attention Layers in Transformers. - Vukasin Bozic; Danilo Dordevic; Daniele Coppola; Joseph Thommes; Sidak Pal Singh (CoRR, 2023)

Rethinking Attention: Exploring Shallow Feed-Forward Neural Networks as an Alternative to Attention Layers in Transformers (Student Abstract). - Danilo Dordevic; Vukasin Bozic; Joseph Thommes; Daniele Coppola; Sidak Pal Singh (AAAI, 2024)

Local vs Global continual learning. - Giulia Lanzillotta; Sidak Pal Singh; Benjamin F. Grewe; Thomas Hofmann (CoLLAs, 2024)

Transformer Fusion with Optimal Transport. - Moritz Imfeld; Jacopo Graldi; Marco Giordano; Thomas Hofmann; Sotiris Anagnostidis; Sidak Pal Singh (ICLR, 2024)

Some Fundamental Aspects about Lipschitz Continuity of Neural Networks. - Grigory Khromov; Sidak Pal Singh (ICLR, 2024)

Towards Meta-Pruning via Optimal Transport. - Alexander Theus; Olin Geimer; Friedrich Wicke; Thomas Hofmann; Sotiris Anagnostidis; Sidak Pal Singh (ICLR, 2024)

Theoretical Characterisation of the Gauss Newton Conditioning in Neural Networks. - Jim Zhao; Sidak Pal Singh; Aurélien Lucchi (NeurIPS, 2024)

Hallmarks of Optimization Trajectories in Neural Networks and LLMs: The Lengths, Bends, and Dead Ends. - Sidak Pal Singh; Bobby He; Thomas Hofmann; Bernhard Schölkopf (CoRR, 2024)

Landscaping Linear Mode Connectivity. - Sidak Pal Singh; Linara Adilova; Michael Kamp; Asja Fischer; Bernhard Schölkopf; Thomas Hofmann (CoRR, 2024)

What Does It Mean to Be a Transformer? Insights from a Theoretical Hessian Analysis. - Weronika Ormaniec; Felix Dangel; Sidak Pal Singh (ICLR, 2025)

The Directionality of Optimization Trajectories in Neural Networks. - Sidak Pal Singh; Bobby He; Thomas Hofmann; Bernhard Schölkopf (ICLR, 2025)

Avoiding spurious sharpness minimization broadens applicability of SAM. - Sidak Pal Singh; Hossein Mobahi; Atish Agarwala; Yann N. Dauphin (CoRR, 2025)

Accelerating Neural Network Training Along Sharp and Flat Directions. - Daniyar Zakarin; Sidak Pal Singh (CoRR, 2025)

Generalized Linear Mode Connectivity for Transformers. - Alexander Theus; Alessandro Cabodi; Sotiris Anagnostidis; Antonio Orvieto; Sidak Pal Singh; Valentina Boeva (CoRR, 2025)

Model Fusion via Neuron Interpolation. - Phoomraphee Luenam; Andreas Spanopoulos; Amit Sant; Thomas Hofmann; Sotiris Anagnostidis; Sidak Pal Singh (CoRR, 2025)