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Journal of Chemical Information and Modeling
|
March 26, 2019
Machine Learning in Drug Discovery
Günter Klambauer, Sepp Hochreiter, Matthias Rarey
Journal of Chemical Information and Modeling
|
July 19, 2024
Diverse Hits in De Novo Molecule Design: Diversity-Based Comparison of Goal-Directed Generators
Philipp Renz, Sohvi Luukkonen, Günter Klambauer
Journal of Chemical Information and Modeling
|
April 30, 2025
MHNfs: Prompting In-Context Bioactivity Predictions for Low-Data Drug Discovery
Johannes Schimunek, Sohvi Luukkonen, Günter Klambauer
Nucleic Acids Research
|
September 20, 2013
DEXUS: identifying differential expression in RNA-Seq studies with unknown conditions
Günter Klambauer, Thomas Unterthiner, Sepp Hochreiter
Journal of Chemical Information and Modeling
|
January 8, 2024
HyperPCM: Robust Task-Conditioned Modeling of Drug-Target Interactions
Emma Svensson, Pieter-Jan Hoedt, Sepp Hochreiter, et al.
Nature Communications
|
November 13, 2023
CLOOME: contrastive learning unlocks bioimaging databases for queries with chemical structures
Ana Sanchez-Fernandez, Elisabeth Rumetshofer, Sepp Hochreiter, et al.
Journal of Chemical Information and Modeling
|
August 18, 2018
Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery
Kristina Preuer, Philipp Renz, Thomas Unterthiner, et al.
Journal of Chemical Information and Modeling
|
March 7, 2019
Accurate Prediction of Biological Assays with High-Throughput Microscopy Images and Convolutional Networks
Markus Hofmarcher, Elisabeth Rumetshofer, Djork-Arné Clevert, et al.
Chemical Research in Toxicology
|
August 21, 2023
Introduction to the Special Issue: AI Meets Toxicology
Günter Klambauer, Djork-Arné Clevert, Imran Shah, et al.
Drug Discovery Today. Technologies
|
January 2, 2021
On failure modes in molecule generation and optimization
Philipp Renz, Dries Van Rompaey, Jörg Kurt Wegner, et al.
Page
of 4
Search research articles
Search
Showing results (1-10 of 35) with videos related to
Sort By:
Page
of 4
Journal of Chemical Information and Modeling
|
March 26, 2019
Machine Learning in Drug Discovery
Günter Klambauer, Sepp Hochreiter, Matthias Rarey
Journal of Chemical Information and Modeling
|
July 19, 2024
Diverse Hits in De Novo Molecule Design: Diversity-Based Comparison of Goal-Directed Generators
Philipp Renz, Sohvi Luukkonen, Günter Klambauer
Journal of Chemical Information and Modeling
|
April 30, 2025
MHNfs: Prompting In-Context Bioactivity Predictions for Low-Data Drug Discovery
Johannes Schimunek, Sohvi Luukkonen, Günter Klambauer
Nucleic Acids Research
|
September 20, 2013
DEXUS: identifying differential expression in RNA-Seq studies with unknown conditions
Günter Klambauer, Thomas Unterthiner, Sepp Hochreiter
Journal of Chemical Information and Modeling
|
January 8, 2024
HyperPCM: Robust Task-Conditioned Modeling of Drug-Target Interactions
Emma Svensson, Pieter-Jan Hoedt, Sepp Hochreiter, et al.
Nature Communications
|
November 13, 2023
CLOOME: contrastive learning unlocks bioimaging databases for queries with chemical structures
Ana Sanchez-Fernandez, Elisabeth Rumetshofer, Sepp Hochreiter, et al.
Journal of Chemical Information and Modeling
|
August 18, 2018
Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery
Kristina Preuer, Philipp Renz, Thomas Unterthiner, et al.
Journal of Chemical Information and Modeling
|
March 7, 2019
Accurate Prediction of Biological Assays with High-Throughput Microscopy Images and Convolutional Networks
Markus Hofmarcher, Elisabeth Rumetshofer, Djork-Arné Clevert, et al.
Chemical Research in Toxicology
|
August 21, 2023
Introduction to the Special Issue: AI Meets Toxicology
Günter Klambauer, Djork-Arné Clevert, Imran Shah, et al.
Drug Discovery Today. Technologies
|
January 2, 2021
On failure modes in molecule generation and optimization
Philipp Renz, Dries Van Rompaey, Jörg Kurt Wegner, et al.
Page
of 4