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ORCIDMohammadamin Tavakoli
- > Home > Persons > Mohammadamin Tavakoli
Publications
- 2025
[j5]Mohammadamin Tavakoli, Yin Ting T. Chiu
, Ann Marie Carlton, David Van Vranken, Pierre Baldi:
Chemically Informed Deep Learning for Interpretable Radical Reaction Prediction. J. Chem. Inf. Model. 65(3): 1228-1242 (2025)- 2024
- [j4]Mohammadamin Tavakoli, Ryan J. Miller, Mirana Angel, Michael A. Pfeiffer, Eugene S. Gutman, Aaron Mood, David Van Vranken, Pierre Baldi:
PMechDB: A Public Database of Elementary Polar Reaction Steps. J. Chem. Inf. Model. 64(6): 1975-1983 (2024) - [i8]Shahriar Hojjati Emmami, Ali Pilehvar Meibody, Lobat Tayebi, Mohammadamin Tavakoli, Pierre Baldi:
Unraveling the Molecular Magic: AI Insights on the Formation of Extraordinarily Stretchable Hydrogels. CoRR abs/2403.05129 (2024) - 2023
- [j3]Mohammadamin Tavakoli, Yin Ting T. Chiu, Pierre Baldi, Ann Marie Carlton, David Van Vranken:
RMechDB: A Public Database of Elementary Radical Reaction Steps. J. Chem. Inf. Model. 63(4): 1114-1123 (2023) - [c2]Mohammadamin Tavakoli, Pierre Baldi, Ann Marie Carlton, Yin Ting T. Chiu, Alexander Shmakov, David Van Vranken:
AI for Interpretable Chemistry: Predicting Radical Mechanistic Pathways via Contrastive Learning. NeurIPS 2023 - [i7]Mohammadamin Tavakoli, Yin Ting T. Chiu, Alexander Shmakov, Ann Marie Carlton, David Van Vranken, Pierre Baldi:
AI for Interpretable Chemistry: Predicting Radical Mechanistic Pathways via Contrastive Learning. CoRR abs/2311.01118 (2023) - 2022
- [j2]Mohammadamin Tavakoli, Aaron Mood, David Van Vranken, Pierre Baldi:
Quantum Mechanics and Machine Learning Synergies: Graph Attention Neural Networks to Predict Chemical Reactivity. J. Chem. Inf. Model. 62(9): 2121-2132 (2022) - [i6]Mohammadamin Tavakoli, Alexander Shmakov, Francesco Ceccarelli, Pierre Baldi:
Rxn Hypergraph: a Hypergraph Attention Model for Chemical Reaction Representation. CoRR abs/2201.01196 (2022) - [i5]Alexander Shmakov, Mohammadamin Tavakoli, Pierre Baldi, Christopher M. Karwin, Alex Broughton, Simona Murgia:
Deep Learning Models of the Discrete Component of the Galactic Interstellar Gamma-Ray Emission. CoRR abs/2206.02819 (2022) - 2021
- [j1]Mohammadamin Tavakoli, Forest Agostinelli, Pierre Baldi:
SPLASH: Learnable activation functions for improving accuracy and adversarial robustness. Neural Networks 140: 1-12 (2021) - [i4]Mohammadamin Tavakoli, Aaron Mood, David Van Vranken, Pierre Baldi:
Quantum Mechanics and Machine Learning Synergies: Graph Attention Neural Networks to Predict Chemical Reactivity. CoRR abs/2103.14536 (2021) - [i3]Mohammadamin Tavakoli, Peter J. Sadowski, Pierre Baldi:
Tourbillon: a Physically Plausible Neural Architecture. CoRR abs/2107.06424 (2021) - 2020
- [c1]Mohammadamin Tavakoli, Pierre Baldi:
Continuous Representation of Molecules using Graph Variational Autoencoder. AAAI Spring Symposium: MLPS 2020 - [i2]Mohammadamin Tavakoli, Pierre Baldi:
Continuous Representation of Molecules Using Graph Variational Autoencoder. CoRR abs/2004.08152 (2020) - [i1]Mohammadamin Tavakoli, Forest Agostinelli, Pierre Baldi:
SPLASH: Learnable Activation Functions for Improving Accuracy and Adversarial Robustness. CoRR abs/2006.08947 (2020)
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