Search Results for author: Philipp Seidl

Found 8 papers, 7 papers with code

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

1 code implementation6 Mar 2023 Philipp Seidl, Andreu Vall, Sepp Hochreiter, Günter Klambauer

Activity and property prediction models are the central workhorses in drug discovery and materials sciences, but currently they have to be trained or fine-tuned for new tasks.

Activity Prediction Attribute +3

Re-evaluating Retrosynthesis Algorithms with Syntheseus

1 code implementation30 Oct 2023 Krzysztof Maziarz, Austin Tripp, Guoqing Liu, Megan Stanley, Shufang Xie, Piotr Gaiński, Philipp Seidl, Marwin Segler

The planning of how to synthesize molecules, also known as retrosynthesis, has been a growing focus of the machine learning and chemistry communities in recent years.

Benchmarking Multi-step retrosynthesis +1

Context-enriched molecule representations improve few-shot drug discovery

1 code implementation24 Apr 2023 Johannes Schimunek, Philipp Seidl, Lukas Friedrich, Daniel Kuhn, Friedrich Rippmann, Sepp Hochreiter, Günter Klambauer

Our novel concept for molecule representation enrichment is to associate molecules from both the support set and the query set with a large set of reference (context) molecules through a Modern Hopfield Network.

Drug Discovery Few-Shot Learning

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

no code implementations26 Apr 2022 Alexander Brunhuemer, Lukas Larcher, Philipp Seidl, Sascha Desmettre, Johannes Kofler, Gerhard Larcher

In this working paper we present our current progress in the training of machine learning models to execute short option strategies on the S&P500.

BIG-bench Machine Learning

Cannot find the paper you are looking for? You can Submit a new open access paper.