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ORCIDArghya Bhowmik
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2020 – today
- 2026
[i12]Jonas Elsborg, Felix Ærtebjerg, Luca A. Thiede, Alán Aspuru-Guzik, Tejs Vegge, Arghya Bhowmik:
Global Plane Waves From Local Gaussians: Periodic Charge Densities in a Blink. CoRR abs/2601.19966 (2026)- [i11]Bjarke Hastrup, François R. J. Cornet, Tejs Vegge, Arghya Bhowmik:
AtomComposer: Discovering Chemical Space from First Principles with Reinforcement Learning. CoRR abs/2605.28287 (2026) - 2025
- [j8]Pol Febrer
, Peter Bjørn Jørgensen, Miguel Pruneda, Alberto García, Pablo Ordejón, Arghya Bhowmik:
Graph2Mat: universal graph to matrix conversion for electron density prediction. Mach. Learn. Sci. Technol. 6(2): 25013 (2025) - [j7]François R. J. Cornet, Pratham Deshmukh, Bardi Benediktsson, Mikkel N. Schmidt, Arghya Bhowmik:
Improving generative inverse design of molecular catalysts in small data regime. Mach. Learn. Sci. Technol. 6(2): 25057 (2025) - [c1]François R. J. Cornet, Federico Bergamin, Arghya Bhowmik, Juan Maria Garcia Lastra, Jes Frellsen, Mikkel N. Schmidt:
Kinetic Langevin Diffusion for Crystalline Materials Generation. ICML 2025 - [i10]Jonas Elsborg, Luca A. Thiede, Alán Aspuru-Guzik, Tejs Vegge, Arghya Bhowmik:
ELECTRA: A Symmetry-breaking Cartesian Network for Charge Density Prediction with Floating Orbitals. CoRR abs/2503.08305 (2025) - [i9]Jonas Elsborg, Tejs Vegge, Arghya Bhowmik:
Acoustic Classification of Maritime Vessels using Learnable Filterbanks. CoRR abs/2505.23964 (2025) - [i8]François R. J. Cornet, Federico Bergamin, Arghya Bhowmik, Juan Maria Garcia Lastra, Jes Frellsen, Mikkel N. Schmidt:
Kinetic Langevin Diffusion for Crystalline Materials Generation. CoRR abs/2507.03602 (2025) - [i7]Andreas Burger, Luca A. Thiede, Nikolaj Rønne, Varinia Bernales, Nandita Vijaykumar, Tejs Vegge, Arghya Bhowmik, Alán Aspuru-Guzik:
Shoot from the HIP: Hessian Interatomic Potentials without derivatives. CoRR abs/2509.21624 (2025) - [i6]Nikolaj Rønne, Tejs Vegge, Arghya Bhowmik:
GO-Diff: Data-free and amortized global structure optimization. CoRR abs/2510.13448 (2025) - [i5]Jonas Elsborg, Arghya Bhowmik:
Reinforcement Learning for Chemical Ordering in Alloy Nanoparticles. CoRR abs/2511.12260 (2025) - 2024
- [j6]Stefan N. Heinen, Danish Khan, Guido Falk von Rudorff, Konstantin Karandashev, Daniel J. Arismendi-Arrieta, Alastair J. A. Price, Surajit Nandi, Arghya Bhowmik, Kersti Hermansson, O. Anatole von Lilienfeld:
Reducing training data needs with minimal multilevel machine learning (M3L). Mach. Learn. Sci. Technol. 5(2): 25058 (2024) - [j5]Jonas Elsborg, Arghya Bhowmik:
ArtiSAN: navigating the complexity of material structures with deep reinforcement learning. Mach. Learn. Sci. Technol. 5(3): 35043 (2024) - 2023
- [j4]Jonas Elsborg, Arghya Bhowmik:
Equivariant Graph-Representation-Based Actor-Critic Reinforcement Learning for Nanoparticle Design. J. Chem. Inf. Model. 63(12): 3731-3741 (2023) - 2022
- [j3]Surajit Nandi, Jonas Busk, Peter Bjørn Jørgensen, Tejs Vegge, Arghya Bhowmik:
Cheap Turns Superior: A Linear Regression-Based Correction Method to Reaction Energy from the DFT. J. Chem. Inf. Model. 62(19): 4727-4735 (2022) - [j2]Jonas Busk, Peter Bjørn Jørgensen, Arghya Bhowmik, Mikkel N. Schmidt, Ole Winther, Tejs Vegge:
Calibrated uncertainty for molecular property prediction using ensembles of message passing neural networks. Mach. Learn. Sci. Technol. 3(1): 15012 (2022) - [j1]Mathias Schreiner, Arghya Bhowmik, Tejs Vegge, Peter Bjørn Jørgensen, Ole Winther:
NeuralNEB - neural networks can find reaction paths fast. Mach. Learn. Sci. Technol. 3(4): 45022 (2022) - [i4]Mathias Schreiner, Arghya Bhowmik, Tejs Vegge, Ole Winther:
NeuralNEB - Neural Networks can find Reaction Paths Fast. CoRR abs/2207.09971 (2022) - [i3]Mathias Schreiner, Arghya Bhowmik, Tejs Vegge, Jonas Busk, Ole Winther:
Transition1x - a Dataset for Building Generalizable Reactive Machine Learning Potentials. CoRR abs/2207.12858 (2022) - 2021
- [i2]Jonas Busk, Peter Bjørn Jørgensen, Arghya Bhowmik, Mikkel N. Schmidt, Ole Winther, Tejs Vegge:
Calibrated Uncertainty for Molecular Property Prediction using Ensembles of Message Passing Neural Networks. CoRR abs/2107.06068 (2021) - 2020
- [i1]Peter Bjørn Jørgensen, Arghya Bhowmik:
DeepDFT: Neural Message Passing Network for Accurate Charge Density Prediction. CoRR abs/2011.03346 (2020)
Coauthor Index
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