Upcoming meetings:

Past meetings:

13.05.2019

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.

13.02.2019

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

03.12.2018

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

26.06.2018

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

30.05.2018

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

16.05.2018

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

04.04.2018

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

21.03.2018

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

14.02.2018

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

23.01.2018

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

10.01.2018

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

13.12.2017

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

22.11.2017

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