Sabyasachi Chakraborty

Guided diffusion for inverse molecular design

Tomer Weiss, Eduardo Mayo Yanes, Sabyasachi Chakraborty et al. · Nature Computational Science · 2023 · 63 citations · Full text

Inverse Molecular Design, Engineering, Applied Physics +7

The chemical space of B, N-substituted polycyclic aromatic hydrocarbons: Combinatorial enumeration and high-throughput first-principles modeling

Sabyasachi Chakraborty, Prakriti Kayastha, Raghunathan Ramakrishnan · The Journal of Chemical Physics · 2019 · 26 citations · Full text

Combinatorial Chemistry, Engineering, High-throughput First-principles +19

Revving up ¹³C NMR shielding predictions across chemical space: benchmarks for atoms-in-molecules kernel machine learning with new data for 134 kilo molecules

Amit Gupta, Sabyasachi Chakraborty, Raghunathan Ramakrishnan · Machine Learning Science and Technology · 2021 · 26 citations · Full text

Engineering, Machine Learning, Magnetic Resonance +20

Data-driven modeling of S₀ → S₁ excitation energy in the BODIPY chemical space: High-throughput computation, quantum machine learning, and inverse design.

Amit Gupta, Sabyasachi Chakraborty, Debashree Ghosh et al. · PubMed · 2021 · 22 citations

Critical benchmarking of popular composite thermochemistry models and density functional approximations on a probabilistically pruned benchmark dataset of formation enthalpies

Sambit Das, Sabyasachi Chakraborty, Raghunathan Ramakrishnan · The Journal of Chemical Physics · 2021 · 19 citations · Full text