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2020 – today
- 2024
[j9]Ganna Gryn'ova
, Tristan Bereau, Carolin Müller, Pascal Friederich, Rebecca C. Wade, Ariane Nunes-Alves, Thereza A. Soares, Kenneth M. Merz Jr.:
EDITORIAL: Chemical Compound Space Exploration by Multiscale High-Throughput Screening and Machine Learning. J. Chem. Inf. Model. 64(15): 5737-5738 (2024)- [c6]Jannik Deuschel, Caleb Ellington, Yingtao Luo, Benjamin J. Lengerich, Pascal Friederich, Eric P. Xing:
Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning. ICML 2024 - [c5]Henrik Schopmans, Pascal Friederich:
Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations. ICML 2024 - [i20]Henrik Schopmans, Pascal Friederich:
Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations. CoRR abs/2402.01195 (2024) - [i19]Jonas Teufel, Pascal Friederich:
Global Concept Explanations for Graphs by Contrastive Learning. CoRR abs/2404.16532 (2024) - 2023
- [j8]Artem Fediai, Patrick Reiser, Jorge Enrique Olivares Peña, Wolfgang Wenzel, Pascal Friederich:
Interpretable delta-learning of GW quasiparticle energies from GGA-DFT. Mach. Learn. Sci. Technol. 4(3): 35045 (2023) - [c4]Jonas Teufel, Luca Torresi, Patrick Reiser, Pascal Friederich:
MEGAN: Multi-explanation Graph Attention Network. xAI (2) 2023: 338-360 - [c3]Jonas Teufel, Luca Torresi, Pascal Friederich:
Quantifying the Intrinsic Usefulness of Attributional Explanations for Graph Neural Networks with Artificial Simulatability Studies. xAI (2) 2023: 361-381 - [i18]Robin Ruff, Patrick Reiser, Jan Stühmer, Pascal Friederich:
Connectivity Optimized Nested Graph Networks for Crystal Structures. CoRR abs/2302.14102 (2023) - [i17]Henrik Schopmans, Patrick Reiser, Pascal Friederich:
Neural networks trained on synthetically generated crystals can extract structural information from ICSD powder X-ray diffractograms. CoRR abs/2303.11699 (2023) - [i16]Jonas Teufel, Luca Torresi, Pascal Friederich:
Quantifying the Intrinsic Usefulness of Attributional Explanations for Graph Neural Networks with Artificial Simulatability Studies. CoRR abs/2305.15961 (2023) - [i15]Hunter Sturm, Jonas Teufel, Kaitlin A. Isfeld, Pascal Friederich, Rebecca L. Davis:
Mitigating Molecular Aggregation in Drug Discovery with Predictive Insights from Explainable AI. CoRR abs/2306.02206 (2023) - [i14]Jannik Deuschel, Caleb N. Ellington, Benjamin J. Lengerich, Yingtao Luo, Pascal Friederich, Eric P. Xing:
Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning. CoRR abs/2310.07918 (2023) - 2022
- [j7]Devon P. Holst, Pascal Friederich, Alán Aspuru-Guzik, Timothy P. Bender:
Updated Calibrated Model for the Prediction of Molecular Frontier Orbital Energies and Its Application to Boron Subphthalocyanines. J. Chem. Inf. Model. 62(4): 829-840 (2022) - [j6]Mario Krenn, Qianxiang Ai, Senja Barthel, Nessa Carson, Angelo Frei, Nathan C. Frey, Pascal Friederich, Théophile Gaudin, Alberto Alexander Gayle, Kevin Maik Jablonka, Rafael F. Lameiro, Dominik Lemm, Alston Lo, Seyed Mohamad Moosavi, José Manuel Nápoles-Duarte, AkshatKumar Nigam, Robert Pollice, Kohulan Rajan, Ulrich Schatzschneider, Philippe Schwaller, Marta Skreta, Berend Smit, Felix Strieth-Kalthoff, Chong Sun, Gary Tom, Guido Falk von Rudorff, Andrew Wang, Andrew D. White, Adamo Young, Rose Yu, Alán Aspuru-Guzik:
SELFIES and the future of molecular string representations. Patterns 3(10): 100588 (2022) - [i13]Mario Krenn, Qianxiang Ai, Senja Barthel, Nessa Carson, Angelo Frei, Nathan C. Frey, Pascal Friederich, Théophile Gaudin, Alberto Alexander Gayle, Kevin Maik Jablonka, Rafael F. Lameiro, Dominik Lemm, Alston Lo, Seyed Mohamad Moosavi, José Manuel Nápoles-Duarte, AkshatKumar Nigam, Robert Pollice, Kohulan Rajan, Ulrich Schatzschneider, Philippe Schwaller, Marta Skreta, Berend Smit, Felix Strieth-Kalthoff, Chong Sun, Gary Tom, Guido Falk von Rudorff, Andrew Wang, Andrew D. White, Adamo Young, Rose Yu, Alán Aspuru-Guzik:
SELFIES and the future of molecular string representations. CoRR abs/2204.00056 (2022) - [i12]Mario Krenn, Robert Pollice, Si Yue Guo, Matteo Aldeghi, Alba Cervera-Lierta, Pascal Friederich, Gabriel dos Passos Gomes, Florian Häse, Adrian Jinich, AkshatKumar Nigam, Zhenpeng Yao, Alán Aspuru-Guzik:
On scientific understanding with artificial intelligence. CoRR abs/2204.01467 (2022) - [i11]Patrick Reiser, Marlen Neubert, André Eberhard, Luca Torresi, Chen Zhou, Chen Shao, Houssam Metni, Clint van Hoesel, Henrik Schopmans, Timo Sommer, Pascal Friederich:
Graph neural networks for materials science and chemistry. CoRR abs/2208.09481 (2022) - [i10]Chen Shao, Zhou Chen, Pascal Friederich:
Graph neural networks to learn joint representations of disjoint molecular graphs. CoRR abs/2210.09517 (2022) - [i9]Jonas Teufel, Luca Torresi, Patrick Reiser, Pascal Friederich:
MEGAN: Multi-Explanation Graph Attention Network. CoRR abs/2211.13236 (2022) - [i8]André Eberhard, Houssam Metni, Georg Fahland, Alexander Stroh, Pascal Friederich:
Actively Learning Costly Reward Functions for Reinforcement Learning. CoRR abs/2211.13260 (2022) - 2021
- [j5]Pascal Friederich, Salvador León, José Darío Perea, Loïc M. Roch, Alán Aspuru-Guzik:
The influence of sorbitol doping on aggregation and electronic properties of PEDOT: PSS: a theoretical study. Mach. Learn. Sci. Technol. 2(1): 01 (2021) - [j4]Pascal Friederich, Mario Krenn, Isaac Tamblyn, Alán Aspuru-Guzik:
Scientific intuition inspired by machine learning-generated hypotheses. Mach. Learn. Sci. Technol. 2(2): 25027 (2021) - [j3]Daniel Flam-Shepherd, Tony C. Wu, Pascal Friederich, Alán Aspuru-Guzik:
Neural message passing on high order paths. Mach. Learn. Sci. Technol. 2(4): 45009 (2021) - [j2]Patrick Reiser, André Eberhard, Pascal Friederich:
Graph neural networks in TensorFlow-Keras with RaggedTensor representation (kgcnn). Softw. Impacts 9: 100095 (2021) - [i7]Matthias Schniewind, Alexander Stroh, Bradley P. Ladewig, Pascal Friederich:
Machine learning for rapid discovery of laminar flow channel wall modifications that enhance heat transfer. CoRR abs/2101.08130 (2021) - [i6]Patrick Reiser, Manuel Konrad, Artem Fediai, Salvador León, Wolfgang Wenzel, Pascal Friederich:
Analyzing dynamical disorder for charge transport in organic semiconductors via machine learning. CoRR abs/2102.01479 (2021) - [i5]Patrick Reiser, André Eberhard, Pascal Friederich:
Implementing graph neural networks with TensorFlow-Keras. CoRR abs/2103.04318 (2021) - 2020
- [j1]Mario Krenn, Florian Häse, AkshatKumar Nigam, Pascal Friederich, Alán Aspuru-Guzik:
Self-referencing embedded strings (SELFIES): A 100% robust molecular string representation. Mach. Learn. Sci. Technol. 1(4): 45024 (2020) - [c2]AkshatKumar Nigam, Pascal Friederich, Mario Krenn, Alán Aspuru-Guzik:
Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space. ICLR 2020 - [i4]Daniel Flam-Shepherd, Tony C. Wu, Pascal Friederich, Alán Aspuru-Guzik:
Neural Message Passing on High Order Paths. CoRR abs/2002.10413 (2020) - [i3]Pascal Friederich, Mario Krenn, Isaac Tamblyn, Alán Aspuru-Guzik:
Scientific intuition inspired by machine learning generated hypotheses. CoRR abs/2010.14236 (2020)
2010 – 2019
- 2019
- [i2]Mario Krenn, Florian Häse, AkshatKumar Nigam, Pascal Friederich, Alán Aspuru-Guzik:
SELFIES: a robust representation of semantically constrained graphs with an example application in chemistry. CoRR abs/1905.13741 (2019) - [i1]AkshatKumar Nigam, Pascal Friederich, Mario Krenn, Alán Aspuru-Guzik:
Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space. CoRR abs/1909.11655 (2019) - 2016
- [c1]Pascal Friederich, Timo Strunk, Wolfgang Wenzel, Ivan Kondov:
Multiscale Simulation of Organic Electronics Via Smart Scheduling of Quantum Mechanics Computations. ICCS 2016: 1244-1254
Coauthor Index
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last updated on 2024-10-07 22:06 CEST by the dblp team
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