Mohammadamin Tavakoli

According to our database, Mohammadamin Tavakoli authored at least 9 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Unraveling the Molecular Magic: AI Insights on the Formation of Extraordinarily Stretchable Hydrogels.

Shahriar Hojjati Emmami, Ali Pilehvar Meibody, Lobat Tayebi, Mohammadamin Tavakoli, Pierre Baldi

CoRR, 2024

2023

RMechDB: A Public Database of Elementary Radical Reaction Steps.

Mohammadamin Tavakoli, Yin Ting T. Chiu, Pierre Baldi, Ann Marie Carlton, David Van Vranken

J. Chem. Inf. Model., February, 2023

AI for Interpretable Chemistry: Predicting Radical Mechanistic Pathways via Contrastive Learning.

Mohammadamin Tavakoli, Pierre Baldi, Ann Marie Carlton, Yin Ting T. Chiu, Alexander Shmakov, David Van Vranken

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Quantum Mechanics and Machine Learning Synergies: Graph Attention Neural Networks to Predict Chemical Reactivity.

Mohammadamin Tavakoli, Aaron Mood, David Van Vranken, Pierre Baldi

J. Chem. Inf. Model., 2022

Deep Learning Models of the Discrete Component of the Galactic Interstellar Gamma-Ray Emission.

Alexander Shmakov, Mohammadamin Tavakoli, Pierre Baldi, Christopher M. Karwin, Alex Broughton, Simona Murgia

CoRR, 2022

Rxn Hypergraph: a Hypergraph Attention Model for Chemical Reaction Representation.

Mohammadamin Tavakoli, Alexander Shmakov, Francesco Ceccarelli, Pierre Baldi

CoRR, 2022

2021

SPLASH: Learnable activation functions for improving accuracy and adversarial robustness.

Mohammadamin Tavakoli, Forest Agostinelli, Pierre Baldi

Neural Networks, 2021

Tourbillon: a Physically Plausible Neural Architecture.

Mohammadamin Tavakoli, Peter J. Sadowski, Pierre Baldi

CoRR, 2021

2020

Continuous Representation of Molecules using Graph Variational Autoencoder.

Mohammadamin Tavakoli, Pierre Baldi

Proceedings of the AAAI 2020 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 23rd - to, 2020