Upcoming meetings:

Past meetings:


Dr. Henrik Seidel, Dr. Djork-Arné Clevert, and Robin Winter, Bayer AI. Learning continuous and data-driven molecular descriptors by translating equivalent chemical representations.
Dr. Wolfgang Kopp, Akalin/Ohler Labs Janggu - a python package for DL in genomics.
Jonathan Ronen, Akalin Lab. Maui - Evaluation of colorectal cancer subtypes and cell lines using deep learning.
Ella Bahry, Preibisch Lab. CNN based approach for accurate drosophila wing registration.


Alf Wachsmann, Scientific Computing, MDC. Deep Learning Resources at MDC. view slides


Uwe Schmidt and Martin Weigert, Myers Lab, MPI-CBG. Deep learning based image restoration and cell segmentation for fluorescence microscopy.


Dagmar Kainmueller, MDC. Mapping Auto-context Decision Forests to Deep ConvNets.


Remo Monti, Lippert Lab, MDC. Deep Learning for Clinical Brain MRI Segmentation - a Comparison of 2D Convolutional Models, 3D Convolutional Models and More. view slides


Frederik Pahde, SAP Berlin. Cross-modal Hallucination for Few-Shot Learning.


Bastiaan Spanjaard, Junker Lab, MDC. Journal club: DeepCpG: accurate prediction of single-cell DNA methylation states using deep learning.


Jonathan Ronen, Akalin Lab, MDC. Variational autoencoders. view slides


Vedran Franke, Akalin Lab, MDC. Sequence Embedding Models in Biology.


Wolfgang Kopp, Akalin Lab, MDC. Transcription Factor Binding Prediction using Deep Learning.
Marwan Zouinkhi, Preibisch Lab, MDC. One Shot Training.


Masha Ghanbari, Ohler Lab, MDC. Application of deep learning for genomics.


Ella Bahry, Preibisch Lab, MDC. Journal club: U-Net: Convolutional Networks for Biomedical Image Segmentation. paper link, view slides


Ella Bahry, Preibisch Lab, MDC. General Intro to Deep Learning.view slides
Klim Kolyvanov, Preibisch Lab, MDC. MNIST Demo with Keras. github link