Pascal Friederich

56 papers A* 4Misc 1Journal 47Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Efficient Training of Boltzmann Generators Using Off-Policy Log-Dispersion Regularization. CoRR Henrik Schopmans, Christopher von Klitzing, Pascal Friederich
2026	J	`jnl`	Graph Recognition via Subgraph Prediction. CoRR André Eberhard, Gerhard Neumann, Pascal Friederich
2025	J	`jnl`	A self-driving lab for solution-processed electrochromic thin films. CoRR Selma Dahms, Luca Torresi, Shahbaz Tareq Bandesha, Jan Hansmann, Holger Röhm, Alexander Colsmann, Marco Schott, Pascal Friederich
2025	J	`jnl`	Advancing Aqueous Solubility Prediction: A Machine Learning Approach for Organic Compounds Using a Curated Data Set. J. Chem. Inf. Model. Mushtaq Ali, Sylvia Vanderheiden, Christoph W. Grathwol, Konrad Krämer, Pascal Friederich, Nicole Jung, Stefan Bräse
2025	J	`jnl`	Generative models for crystalline materials. CoRR Houssam Metni, Laura Ruple, Lauren N. Walters, Luca Torresi, Jonas Teufel, Henrik Schopmans, Jona Östreicher, Yumeng Zhang, Marlen Neubert, Yuri Koide, Kevin Steiner, Paul Link, Lukas Bär, Mariana Petrova, Gerbrand Ceder, Pascal Friederich
2025	—	`conf`	Improving Counterfactual Truthfulness for Molecular Property Prediction Through Uncertainty Quantification. xAI (5) Jonas Teufel, Annika Leinweber, Pascal Friederich
2025	J	`jnl`	Improving Counterfactual Truthfulness for Molecular Property Prediction through Uncertainty Quantification. CoRR Jonas Teufel, Annika Leinweber, Pascal Friederich
2025	J	`jnl`	Infrared spectrum analysis of organic molecules with neural networks using standard reference data sets in combination with real-world data. J. Cheminformatics Dev Punjabi, Yu-Chieh Huang, Laura Holzhauer, Pierre Tremouilhac, Pascal Friederich, Nicole Jung, Stefan Bräse
2025	J	`jnl`	Learning Boltzmann Generators via Constrained Mass Transport. CoRR Christopher von Klitzing, Denis Blessing, Henrik Schopmans, Pascal Friederich, Gerhard Neumann
2025	J	`jnl`	Learning Potential Energy Surfaces of Hydrogen Atom Transfer Reactions in Peptides. CoRR Marlen Neubert, Patrick Reiser, Frauke Gräter, Pascal Friederich
2025	J	`jnl`	Multi-stage Bayesian optimisation for dynamic decision-making in self-driving labs. CoRR Luca Torresi, Pascal Friederich
2025	J	`jnl`	Predicting New Research Directions in Materials Science using Large Language Models and Concept Graphs. CoRR Thomas Marwitz, Alexander Colsmann, Ben Breitung, Christoph Brabec, Christoph Kirchlechner, Eva Blasco, Gabriel Cadilha Marques, Horst Hahn, Michael Hirtz, Pavel A. Levkin, Yolita M. Eggeler, Tobias Schlöder, Pascal Friederich
2025	J	`jnl`	Symmetry-Aware Bayesian Flow Networks for Crystal Generation. CoRR Laura Ruple, Luca Torresi, Henrik Schopmans, Pascal Friederich
2025	A*	`conf`	Temperature-Annealed Boltzmann Generators. ICML Henrik Schopmans, Pascal Friederich
2025	J	`jnl`	Temperature-Annealed Boltzmann Generators. CoRR Henrik Schopmans, Pascal Friederich
2025	J	`jnl`	The Black Hole Strategy: Gravity-Based Representative Sampling for Frugal Graph Learning on Metal-Organic Framework Networks. J. Chem. Inf. Model. Mehrdad Jalali, A. D. Dinga Wonanke, Pascal Friederich, Christof Wöll
2025	J	`jnl`	Towards a fully differentiable digital twin for solar cells. CoRR Marie Louise Schubert, Houssam Metni, Jan David Fischbach, Benedikt Zerulla, Marjan Krstic, Ulrich W. Paetzold, Seyedamir Orooji, Olivier J. J. Ronsin, Yasin Ameslon, Jens Harting, Thomas Kirchartz, Sandheep Ravishankar, Chris Dreessen, Eunchi Kim, Christian Sprau, Mohamed Hussein, Alexander Colsmann, Karen Forberich, Klaus Jäger, Pascal Friederich, Carsten Rockstuhl
2025	J	`jnl`	opXRD: Open Experimental Powder X-ray Diffraction Database. CoRR Daniel Hollarek, Henrik Schopmans, Jona Östreicher, Jonas Teufel, Bin Cao, Adie Alwen, Simon Schweidler, Mriganka Singh, Tim Kodalle, Hanlin Hu, Gregoire Heymans, Maged Abdelsamie, Arthur Hardiagon, Alexander Wieczorek, Siarhei Zhuk, Ruth Schwaiger, Sebastian Siol, François-Xavier Coudert, Moritz Wolf, Carolin M. Sutter-Fella, Ben Breitung, Andrea M. Hodge, Tong-yi Zhang, Pascal Friederich
2024	J	`jnl`	Actively learning costly reward functions for reinforcement learning. Mach. Learn. Sci. Technol. André Eberhard, Houssam Metni, Georg Fahland, Alexander Stroh, Pascal Friederich
2024	A*	`conf`	Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations. ICML Henrik Schopmans, Pascal Friederich
2024	J	`jnl`	Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations. CoRR Henrik Schopmans, Pascal Friederich
2024	A*	`conf`	Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning. ICML Jannik Deuschel, Caleb Ellington, Yingtao Luo, Benjamin J. Lengerich, Pascal Friederich, Eric P. Xing
2024	J	`jnl`	EDITORIAL: Chemical Compound Space Exploration by Multiscale High-Throughput Screening and Machine Learning. J. Chem. Inf. Model. Ganna Gryn'ova, Tristan Bereau, Carolin Müller, Pascal Friederich, Rebecca C. Wade, Ariane Nunes-Alves, Thereza A. Soares, Kenneth M. Merz Jr.
2024	—	`conf`	Global Concept Explanations for Graphs by Contrastive Learning. xAI (1) Jonas Teufel, Pascal Friederich
2024	J	`jnl`	Global Concept Explanations for Graphs by Contrastive Learning. CoRR Jonas Teufel, Pascal Friederich
2024	J	`jnl`	PAL - Parallel active learning for machine-learned potentials. CoRR Chen Zhou, Marlen Neubert, Yuri Koide, Yumeng Zhang, Van-Quan Vuong, Tobias Schlöder, Stefanie Dehnen, Pascal Friederich
2023	J	`jnl`	Connectivity Optimized Nested Graph Networks for Crystal Structures. CoRR Robin Ruff, Patrick Reiser, Jan Stühmer, Pascal Friederich
2023	J	`jnl`	Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning. CoRR Jannik Deuschel, Caleb N. Ellington, Benjamin J. Lengerich, Yingtao Luo, Pascal Friederich, Eric P. Xing
2023	J	`jnl`	Interpretable delta-learning of GW quasiparticle energies from GGA-DFT. Mach. Learn. Sci. Technol. Artem Fediai, Patrick Reiser, Jorge Enrique Olivares Peña, Wolfgang Wenzel, Pascal Friederich
2023	—	`conf`	MEGAN: Multi-explanation Graph Attention Network. xAI (2) Jonas Teufel, Luca Torresi, Patrick Reiser, Pascal Friederich
2023	J	`jnl`	Mitigating Molecular Aggregation in Drug Discovery with Predictive Insights from Explainable AI. CoRR Hunter Sturm, Jonas Teufel, Kaitlin A. Isfeld, Pascal Friederich, Rebecca L. Davis
2023	J	`jnl`	Neural networks trained on synthetically generated crystals can extract structural information from ICSD powder X-ray diffractograms. CoRR Henrik Schopmans, Patrick Reiser, Pascal Friederich
2023	—	`conf`	Quantifying the Intrinsic Usefulness of Attributional Explanations for Graph Neural Networks with Artificial Simulatability Studies. xAI (2) Jonas Teufel, Luca Torresi, Pascal Friederich
2023	J	`jnl`	Quantifying the Intrinsic Usefulness of Attributional Explanations for Graph Neural Networks with Artificial Simulatability Studies. CoRR Jonas Teufel, Luca Torresi, Pascal Friederich
2022	J	`jnl`	Actively Learning Costly Reward Functions for Reinforcement Learning. CoRR André Eberhard, Houssam Metni, Georg Fahland, Alexander Stroh, Pascal Friederich
2022	J	`jnl`	Graph neural networks for materials science and chemistry. CoRR Patrick Reiser, Marlen Neubert, André Eberhard, Luca Torresi, Chen Zhou, Chen Shao, Houssam Metni, Clint van Hoesel, Henrik Schopmans, Timo Sommer, Pascal Friederich
2022	J	`jnl`	Graph neural networks to learn joint representations of disjoint molecular graphs. CoRR Chen Shao, Zhou Chen, Pascal Friederich
2022	J	`jnl`	MEGAN: Multi-Explanation Graph Attention Network. CoRR Jonas Teufel, Luca Torresi, Patrick Reiser, Pascal Friederich
2022	J	`jnl`	On scientific understanding with artificial intelligence. CoRR 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
2022	J	`jnl`	SELFIES and the future of molecular string representations. CoRR 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
2022	J	`jnl`	SELFIES and the future of molecular string representations. Patterns 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
2022	J	`jnl`	Updated Calibrated Model for the Prediction of Molecular Frontier Orbital Energies and Its Application to Boron Subphthalocyanines. J. Chem. Inf. Model. Devon P. Holst, Pascal Friederich, Alán Aspuru-Guzik, Timothy P. Bender
2021	J	`jnl`	Analyzing dynamical disorder for charge transport in organic semiconductors via machine learning. CoRR Patrick Reiser, Manuel Konrad, Artem Fediai, Salvador León, Wolfgang Wenzel, Pascal Friederich
2021	J	`jnl`	Graph neural networks in TensorFlow-Keras with RaggedTensor representation (kgcnn). Softw. Impacts Patrick Reiser, André Eberhard, Pascal Friederich
2021	J	`jnl`	Implementing graph neural networks with TensorFlow-Keras. CoRR Patrick Reiser, André Eberhard, Pascal Friederich
2021	J	`jnl`	Machine learning for rapid discovery of laminar flow channel wall modifications that enhance heat transfer. CoRR Matthias Schniewind, Alexander Stroh, Bradley P. Ladewig, Pascal Friederich
2021	J	`jnl`	Neural message passing on high order paths. Mach. Learn. Sci. Technol. Daniel Flam-Shepherd, Tony C. Wu, Pascal Friederich, Alán Aspuru-Guzik
2021	J	`jnl`	Scientific intuition inspired by machine learning-generated hypotheses. Mach. Learn. Sci. Technol. Pascal Friederich, Mario Krenn, Isaac Tamblyn, Alán Aspuru-Guzik
2021	J	`jnl`	The influence of sorbitol doping on aggregation and electronic properties of PEDOT: PSS: a theoretical study. Mach. Learn. Sci. Technol. Pascal Friederich, Salvador León, José Darío Perea, Loïc M. Roch, Alán Aspuru-Guzik
2020	A*	`conf`	Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space. ICLR AkshatKumar Nigam, Pascal Friederich, Mario Krenn, Alán Aspuru-Guzik
2020	J	`jnl`	Neural Message Passing on High Order Paths. CoRR Daniel Flam-Shepherd, Tony C. Wu, Pascal Friederich, Alán Aspuru-Guzik
2020	J	`jnl`	Scientific intuition inspired by machine learning generated hypotheses. CoRR Pascal Friederich, Mario Krenn, Isaac Tamblyn, Alán Aspuru-Guzik
2020	J	`jnl`	Self-referencing embedded strings (SELFIES): A 100% robust molecular string representation. Mach. Learn. Sci. Technol. Mario Krenn, Florian Häse, AkshatKumar Nigam, Pascal Friederich, Alán Aspuru-Guzik
2019	J	`jnl`	Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space. CoRR AkshatKumar Nigam, Pascal Friederich, Mario Krenn, Alán Aspuru-Guzik
2019	J	`jnl`	SELFIES: a robust representation of semantically constrained graphs with an example application in chemistry. CoRR Mario Krenn, Florian Häse, AkshatKumar Nigam, Pascal Friederich, Alán Aspuru-Guzik
2016	Misc	`conf`	Multiscale Simulation of Organic Electronics Via Smart Scheduling of Quantum Mechanics Computations. ICCS Pascal Friederich, Timo Strunk, Wolfgang Wenzel, Ivan Kondov