28 citations · 68 across the 6 of their papers we have counts for
6 papers
Spiers Memorial Lecture: How to do impactful research in artificial intelligence for chemistry and materials science
Austin Cheng, Cher Tian Ser, Marta Skreta +8
Machine learning has been pervasively touching many fields of science. Chemistry and materials science are no exception. While machine learning has been making a great impact, it i…
Sorting Out Quantum Monte Carlo
Jack Richter-Powell, Luca Thiede, Alán Asparu-Guzik +1
Molecular modeling at the quantum level requires choosing a parameterization of the wavefunction that both respects the required particle symmetries, and is scalable to systems of…
Towards equilibrium molecular conformation generation with GFlowNets
Alexandra Volokhova, Michał Koziarski, Alex Hernández-García +7
Sampling diverse, thermodynamically feasible molecular conformations plays a crucial role in predicting properties of a molecule. In this paper we propose to use GFlowNet for sampl…
Waveflow: boundary-conditioned normalizing flows applied to fermionic wavefunctions
Luca Thiede, Chong Sun, Alán Aspuru-Guzik
An efficient and expressive wavefunction ansatz is key to scalable solutions for complex many-body electronic structures. While Slater determinants are predominantly used for const…
Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design
AkshatKumar Nigam, Robert Pollice, Gary Tom +5
The efficient exploration of chemical space to design molecules with intended properties enables the accelerated discovery of drugs, materials, and catalysts, and is one of the mos…
Curiosity in exploring chemical space: Intrinsic rewards for deep molecular reinforcement learning
Luca A. Thiede, Mario Krenn, AkshatKumar Nigam +1
Computer-aided design of molecules has the potential to disrupt the field of drug and material discovery. Machine learning, and deep learning, in particular, have been topics where…