34 citations · 88 across the 18 of their papers we have counts for
10 papers · 1 filter
Exact Symmetry as Algebra: A Machine-Verified Tensor Calculus that Enforces Physical Selection Rules
Paulina Hoyos, Shashanka Ubaru, Dongsung Huh +5
Symmetry is central to the physical sciences, yet machine learning usually captures it only approximately, leaving a residual per-step equivariance error that compoun…
Interpretable epistemic uncertainty decomposition in sequential generative models via polynomial chaos surrogates
Ramón Nartallo-Kaluarachchi, Shashanka Ubaru, Małgorzata J Zimoń +4
Sequential generative models conditioned on uncertain rewards are central to AI-driven scientific discovery, yet the epistemic uncertainty they inherit from imperfect reward estima…
Fast Linear Solvers via AI-Tuned Markov Chain Monte Carlo-based Matrix Inversion
Anton Lebedev, Won Kyung Lee, Soumyadip Ghosh +7
Large, sparse linear systems are pervasive in modern science and engineering, and Krylov subspace solvers are an established means of solving them. Yet convergence can be slow for…
Transformers Learn Faster with Semantic Focus
Parikshit Ram, Kenneth L. Clarkson, Tim Klinger +2
Various forms of sparse attention have been explored to mitigate the quadratic computational and memory cost of the attention mechanism in transformers. We study sparse transformer…
Combinatorial Multi-armed Bandits: Arm Selection via Group Testing
Arpan Mukherjee, Shashanka Ubaru, Keerthiram Murugesan +2
This paper considers the problem of combinatorial multi-armed bandits with semi-bandit feedback and a cardinality constraint on the super-arm size. Existing algorithms for solving…
Capacity Analysis of Vector Symbolic Architectures
Kenneth L. Clarkson, Shashanka Ubaru, Elizabeth Yang
Hyperdimensional computing (HDC) is a biologically-inspired framework which represents symbols with high-dimensional vectors, and uses vector operations to manipulate them. The ens…