Philipp Seidl - RankMe

15 papers A* 4Journal 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	MolecularIQ: Characterizing Chemical Reasoning Capabilities Through Symbolic Verification on Molecular Graphs. CoRR Christoph Bartmann, Johannes Schimunek, Mykyta Ielanskyi, Philipp Seidl, Günter Klambauer, Sohvi Luukkonen
2025	A*	`conf`	Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences. ICLR Niklas Schmidinger, Lisa Schneckenreiter, Philipp Seidl, Johannes Schimunek, Pieter-Jan Hoedt, Johannes Brandstetter, Andreas Mayr, Sohvi Luukkonen, Sepp Hochreiter, Günter Klambauer
2025	J	`jnl`	Federated Few-Shot Learning for Epileptic Seizure Detection Under Privacy Constraints. CoRR Ekaterina Sysoykova, Bernhard Anzengruber-Tanase, Michael Haslgrübler, Philipp Seidl, Alois Ferscha
2024	J	`jnl`	Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences. CoRR Niklas Schmidinger, Lisa Schneckenreiter, Philipp Seidl, Johannes Schimunek, Pieter-Jan Hoedt, Johannes Brandstetter, Andreas Mayr, Sohvi Luukkonen, Sepp Hochreiter, Günter Klambauer
2023	A*	`conf`	Context-enriched molecule representations improve few-shot drug discovery. ICLR Johannes Schimunek, Philipp Seidl, Lukas Friedrich, Daniel Kuhn, Friedrich Rippmann, Sepp Hochreiter, Günter Klambauer
2023	J	`jnl`	Context-enriched molecule representations improve few-shot drug discovery. CoRR Johannes Schimunek, Philipp Seidl, Lukas Friedrich, Daniel Kuhn, Friedrich Rippmann, Sepp Hochreiter, Günter Klambauer
2023	A*	`conf`	Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language. ICML Philipp Seidl, Andreu Vall, Sepp Hochreiter, Günter Klambauer
2023	J	`jnl`	Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language. CoRR Philipp Seidl, Andreu Vall, Sepp Hochreiter, Günter Klambauer
2023	J	`jnl`	Re-evaluating Retrosynthesis Algorithms with Syntheseus. CoRR Krzysztof Maziarz, Austin Tripp, Guoqing Liu, Megan Stanley, Shufang Xie, Piotr Gainski, Philipp Seidl, Marwin H. S. Segler
2022	J	`jnl`	Improving Few- and Zero-Shot Reaction Template Prediction Using Modern Hopfield Networks. J. Chem. Inf. Model. Philipp Seidl, Philipp Renz, Natalia Dyubankova, Paulo Neves, Jonas Verhoeven, Jörg K. Wegner, Marwin H. S. Segler, Sepp Hochreiter, Günter Klambauer
2022	J	`jnl`	Supervised machine learning classification for short straddles on the S&P500. CoRR Alexander Brunhuemer, Lukas Larcher, Philipp Seidl, Sascha Desmettre, Johannes Kofler, Gerhard Larcher
2021	A*	`conf`	Hopfield Networks is All You Need. ICLR 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
2021	J	`jnl`	Modern Hopfield Networks for Few- and Zero-Shot Reaction Prediction. CoRR Philipp Seidl, Philipp Renz, Natalia Dyubankova, Paulo Neves, Jonas Verhoeven, Jörg K. Wegner, Sepp Hochreiter, Günter Klambauer
2020	J	`jnl`	Hopfield Networks is All You Need. CoRR 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
2020	J	`jnl`	Large-scale ligand-based virtual screening for SARS-CoV-2 inhibitors using deep neural networks. CoRR Markus Hofmarcher, Andreas Mayr, Elisabeth Rumetshofer, Peter Ruch, Philipp Renz, Johannes Schimunek, Philipp Seidl, Andreu Vall, Michael Widrich, Sepp Hochreiter, Günter Klambauer