Pascal Friederich

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 32

Top Topics

Materials Science

Machine Learning

Top Venues

Mach. Learn. Sci. Technol.

Publications

Jonas Teufel, Pascal Friederich
Global Concept Explanations for Graphs by Contrastive Learning. CoRR (2024)
Henrik Schopmans, Pascal Friederich
Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations. CoRR (2024)
Henrik Schopmans, Patrick Reiser, Pascal Friederich
Neural networks trained on synthetically generated crystals can extract structural information from ICSD powder X-ray diffractograms. CoRR (2023)
Robin Ruff, Patrick Reiser, Jan Stühmer, Pascal Friederich
Connectivity Optimized Nested Graph Networks for Crystal Structures. CoRR (2023)
Jonas Teufel, Luca Torresi, Patrick Reiser, Pascal Friederich
MEGAN: Multi-explanation Graph Attention Network. xAI (2) (2023)
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 (2023)
Jonas Teufel, Luca Torresi, Pascal Friederich
Quantifying the Intrinsic Usefulness of Attributional Explanations for Graph Neural Networks with Artificial Simulatability Studies. CoRR (2023)
Jonas Teufel, Luca Torresi, Pascal Friederich
Quantifying the Intrinsic Usefulness of Attributional Explanations for Graph Neural Networks with Artificial Simulatability Studies. xAI (2) (2023)
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 (2023)
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) (2023)
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 (2022)
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 (2022)
André Eberhard, Houssam Metni, Georg Fahland, Alexander Stroh, Pascal Friederich
Actively Learning Costly Reward Functions for Reinforcement Learning. CoRR (2022)
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) (2022)
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) (2022)
Chen Shao, Zhou Chen, Pascal Friederich
Graph neural networks to learn joint representations of disjoint molecular graphs. CoRR (2022)
Jonas Teufel, Luca Torresi, Patrick Reiser, Pascal Friederich
MEGAN: Multi-Explanation Graph Attention Network. CoRR (2022)
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 (2022)
Patrick Reiser, André Eberhard, Pascal Friederich
Graph neural networks in TensorFlow-Keras with RaggedTensor representation (kgcnn). Softw. Impacts 9 (2021)
Daniel Flam-Shepherd, Tony C. Wu, Pascal Friederich, Alán Aspuru-Guzik
Neural message passing on high order paths. Mach. Learn. Sci. Technol. 2 (4) (2021)
Pascal Friederich, Mario Krenn, Isaac Tamblyn, Alán Aspuru-Guzik
Scientific intuition inspired by machine learning-generated hypotheses. Mach. Learn. Sci. Technol. 2 (2) (2021)
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) (2021)
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 (2021)
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 (2021)
Patrick Reiser, André Eberhard, Pascal Friederich
Implementing graph neural networks with TensorFlow-Keras. CoRR (2021)
AkshatKumar Nigam, Pascal Friederich, Mario Krenn, Alán Aspuru-Guzik
Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space. ICLR (2020)
Daniel Flam-Shepherd, Tony C. Wu, Pascal Friederich, Alán Aspuru-Guzik
Neural Message Passing on High Order Paths. CoRR (2020)
Pascal Friederich, Mario Krenn, Isaac Tamblyn, Alán Aspuru-Guzik
Scientific intuition inspired by machine learning generated hypotheses. CoRR (2020)
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) (2020)
AkshatKumar Nigam, Pascal Friederich, Mario Krenn, Alán Aspuru-Guzik
Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space. CoRR (2019)
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 (2019)
Pascal Friederich, Timo Strunk, Wolfgang Wenzel, Ivan Kondov
Multiscale Simulation of Organic Electronics Via Smart Scheduling of Quantum Mechanics Computations. ICCS (2016)