1 citations · 1 across the 3 of their papers we have counts for
3 papers
Pruning Laws for Large Language Models
Ayan Sengupta, Siddhant Chaudhary, Tanmoy Chakraborty
Scaling up model parameters and training data consistently improves the performance of large language models (LLMs), but at the cost of rapidly growing memory and compute requireme…
Circuit Depth Reduction for Executable Hamiltonian Dynamics of Covalent Inhibitor Reactivity on Quantum Hardware
Marek Kowalik, Sam Genway, Vedangi Pathak +8
Quantum chemistry applications in the noisy intermediate-scale quantum era require end-to-end approaches that balance algorithmic fidelity with practical executability on existing…
Data-driven reactivity prediction of targeted covalent inhibitors using computed quantum features for drug discovery
Tom W. A. Montgomery, Peter Pogány, Alice Purdy +6
We present an approach to combine novel molecular features with experimental data within a data-driven pipeline. The method is applied to the challenge of predicting the reactivity…