Siddharth Mansingh

According to our database, Siddharth Mansingh authored at least 6 papers between 2024 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Out-of-distribution transfer of PDE foundation models to material dynamics under extreme loading.

Mahindra Singh Rautela, Alexander Most, Siddharth Mansingh, Aleksandra Pachalieva, Bradley C. Love, Daniel O'Malley, Alexander Scheinker, Kyle Hickmann, Diane Oyen, Nathan DeBardeleben, Earl Lawrence, Ayan Biswas

CoRR, March, 2026

2025

MORPH: Shape-agnostic PDE Foundation Models.

Mahindra Singh Rautela, Alexander Most, Siddharth Mansingh, Bradley C. Love, Ayan Biswas, Diane Oyen, Earl Lawrence

CoRR, September, 2025

Towards Reasoning for PDE Foundation Models: A Reward-Model-Driven Inference-Time-Scaling Algorithm.

Siddharth Mansingh, James Amarel, Ragib Arnab, Arvind T. Mohan, Kamaljeet Singh, Gerd J. Kunde, Nicolas Hengartner, Benjamin Migliori, Emily Casleton, Nathan DeBardeleben, Ayan Biswas, Diane Oyen, Earl Lawrence

CoRR, September, 2025

Generalization vs. Memorization in Autoregressive Deep Learning: Or, Examining Temporal Decay of Gradient Coherence.

James Amarel, Nicolas Hengartner, Robyn Miller, Kamaljeet Singh, Siddharth Mansingh, Arvind T. Mohan, Benjamin Migliori, Emily Casleton, Alexei N. Skurikhin, Earl Lawrence, Gerd J. Kunde

CoRR, September, 2025

2024

How Robust Are Energy-Based Models Trained With Equilibrium Propagation?

Siddharth Mansingh, Michal Kucer, Garrett T. Kenyon, Juston Moore, Michael A. Teti

CoRR, 2024

Energy-Based Models Trained with Equilibrium Propagation are Inherently Robust.

Siddharth Mansingh, Michal Kucer, Garrett T. Kenyon, Juston Moore, Michael A. Teti

Proceedings of the International Conference on Machine Learning and Applications, 2024