BioLearning_KULeuven @BioLearning_KUL
Research group @KU_Leuven #ESAT #STADIUS (Belgium) focused on #machinelearning #deeplearning and #softwaredevelopment in #Bioinformatics and #Chemoinformatics Leuven, Belgium Joined January 2018-
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Andras Formanek, from our lab, will present tomorrow 20th at #ICANN2024 (14:50, Aula Magna) on Model Based Clustering of Time Series Utilizing Expert ODEs. Paper: link.springer.com/chapter/10.100…
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Daniele Raimondi from our lab gave a highlight talk on the ballance of dataset size and model complexity in genome interpretation on #ECCB2024. You can read the original work at genomebiology.biomedcentral.com/articles/10.11…
BioLearning_KULeuven retweeted
Second talk is by Rosa Friesacher @RosaFriesi from @AstraZeneca and @KU_Leuven speaks about calibration of uncertainty for activity predictions in classification models using time-split validation experiments.
If you are curious how different #uncertainty estimation methods perform when they are tested on NN models trained on large scale industrial #pharma data, visit our poster in room A8 (AI4Science) from 16:15 #ICML2024 @RosaFriesi @adamgld Emma Svensson @AiddOne
Exciting keynote by Prof. David Baker on de-novo protein design #CVPR2024
Please join us today afternoon on #CVPR24 poster section, number 297. To hear about our CV method for extracting chemical knowledge from papers and patents.
Meet us on #2024, Martijn @adamgld
It was a pleasure to have Igor Tetko from Helmholtz Munich presenting us a detailed review of challenges and Advanced ML solutions in Drug Discovery @AiddOne @AiChemist_DN
BioLearning_KULeuven retweeted
Together with @EuNeuralNetSoc, @AiddOne and @AiChemist_DN, we announce the Tox24 Challenge ochem.eu/static/challen… to predict the in vitro toxicity of compounds tested for activity against transthyretin by @EPA Read more: pubs.acs.org/doi/10.1021/ac… Submit your model by AUGUST 31!
Our paper (accepted by #CVPR2024) is now available as a preprint on @arxiv: (arxiv.org/abs/2404.01743). We introduce the first model to perform OCSR with atom-level entity detection with only SMILES supervision. Code is available on @github (github.com/molden/atomlenz).
You can also find us on sigmoid.social as biolearning.
It was a pleasure to welcome @PTorrenPeraire in Leuven, where she gave a talk about her work on the effect of single-step retrosynthesis models on multi-step planning performance. @AiddOne
It was a pleasure to welcome @ana_sanchezf in Leuven, where she gave a talk about her work on Representation learning based on cell painting microscopy images. #AIDDOne
BioLearning_KULeuven retweeted
The AiChemist project has officially started! This boundary-pushing #phd programme brings together experts in #AI, #chemoinformatics and #chemistry from #academia and #pharma to train future #XAI specialists in the life sciences. aichemist.eu/openpositions --> apply until 10.09!
Our work on identifying clusters of dynamical system behaviour is presented today at #ismbeccb2023, Poster C-412.
We present our work on optimal transport for domain adaptation in liquid biopsies today on #ISMBECCB2023, Poster B-310. If you are interested, join us!
Why additive models seem optimal in genetic risk modeling, while we expect nonlinear relationship? If you are interested check our poster at B-234 #ISMBECCB2023
#ISMBECCB2023 is on! Exciting talk on ancient DNA by Janet Kelso.
BioLearning_KULeuven retweeted
AIDD project organized its fifth School at @AstraZeneca during the first week of July. The top scientists of the company and invited speaker provided excellent overview of the progress of AI to speed up drug discovery. Selected lectures will be posted at ai-dd.eu/lectures
BioLearning_KULeuven retweeted
The magnificent @Robert_Weber_ interviewed me for his Artificial Intelligence podcast -- online tomorrow (May 11) here: aipod.de
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