Philipp Seidl

According to our database, Philipp Seidl authored at least 12 papers between 2020 and 2026.

Collaborative distances:

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

2026

MolecularIQ: Characterizing Chemical Reasoning Capabilities Through Symbolic Verification on Molecular Graphs.

Christoph Bartmann, Johannes Schimunek, Mykyta Ielanskyi, Philipp Seidl, Günter Klambauer, Sohvi Luukkonen

CoRR, January, 2026

2025

Federated Few-Shot Learning for Epileptic Seizure Detection Under Privacy Constraints.

Ekaterina Sysoykova, Bernhard Anzengruber-Tanase, Michael Haslgrübler, Philipp Seidl, Alois Ferscha

CoRR, December, 2025

Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences.

Niklas Schmidinger, Lisa Schneckenreiter, Philipp Seidl, Johannes Schimunek, Pieter-Jan Hoedt, Johannes Brandstetter, Andreas Mayr, Sohvi Luukkonen, Sepp Hochreiter, Günter Klambauer

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2023

Re-evaluating Retrosynthesis Algorithms with Syntheseus.

Krzysztof Maziarz, Austin Tripp, Guoqing Liu, Megan Stanley, Shufang Xie, Piotr Gainski, Philipp Seidl, Marwin H. S. Segler

CoRR, 2023

Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language.

Philipp Seidl, Andreu Vall, Sepp Hochreiter, Günter Klambauer

Proceedings of the International Conference on Machine Learning, 2023

Context-enriched molecule representations improve few-shot drug discovery.

Johannes Schimunek, Philipp Seidl, Lukas Friedrich, Daniel Kuhn, Friedrich Rippmann, Sepp Hochreiter, Günter Klambauer

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Improving Few- and Zero-Shot Reaction Template Prediction Using Modern Hopfield Networks.

Philipp Seidl, Philipp Renz, Natalia Dyubankova, Paulo Neves, Jonas Verhoeven, Jörg K. Wegner, Marwin H. S. Segler, Sepp Hochreiter, Günter Klambauer

J. Chem. Inf. Model., 2022

Supervised machine learning classification for short straddles on the S&P500.

Alexander Brunhuemer, Lukas Larcher, Philipp Seidl, Sascha Desmettre, Johannes Kofler, Gerhard Larcher

CoRR, 2022

2021

Modern Hopfield Networks for Few- and Zero-Shot Reaction Prediction.

Philipp Seidl, Philipp Renz, Natalia Dyubankova, Paulo Neves, Jonas Verhoeven, Jörg K. Wegner, Sepp Hochreiter, Günter Klambauer

CoRR, 2021

Hopfield Networks is All You Need.

Hubert Ramsauer, Bernhard Schäfl, Johannes Lehner, Philipp Seidl, Michael Widrich, Lukas Gruber, Markus Holzleitner, Thomas Adler, David P. Kreil, Michael K. Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Hopfield Networks is All You Need.

Hubert Ramsauer, Bernhard Schäfl, Johannes Lehner, Philipp Seidl, Michael Widrich, Lukas Gruber, Markus Holzleitner, Milena Pavlovic, Geir Kjetil Sandve, Victor Greiff, David P. Kreil, Michael Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter

CoRR, 2020

Large-scale ligand-based virtual screening for SARS-CoV-2 inhibitors using deep neural networks.

Markus Hofmarcher, Andreas Mayr, Elisabeth Rumetshofer, Peter Ruch, Philipp Renz, Johannes Schimunek, Philipp Seidl, Andreu Vall, Michael Widrich, Sepp Hochreiter, Günter Klambauer

CoRR, 2020