29.07.2020

Teaser image to MCML - Virtual workshop

MCML - Virtual workshop

Over 20 presentations by our PhD students on current research topics

The workshop includes presentations on Spatial and Temporal Machine Learning & Computer Vision, Learning on Graphs and Networks & Representation Learning, and Automatic and Explainable Modeling & Computational Models for Large-Sclae ML.

Agenda

14:00–
14:20
       Prof. Dr. Thomas Seidl, Prof. Dr. Daniel Cremers
Welcome Greeting


Track 1: Spatial and Temporal Machine Learning & Computer Vision

14:20–
14:40
       Ashkan Khakzar, Azade Farshad / Prof. Dr. Nassir Navab
Machine Learning at CAMP: Interpretability and Spatio-temporal Learning for Medical Imaging

14:40–
15:00
Christopher Küster / Prof. Dr. Volker Schmid
Bayesian image segmentation with hierarchical Potts models

15:00–
15:20
Prof. Dr. Matthias Schubert
Resource Search in Data Driven Environments

15:20–
15:40
Guillem Brasó / Prof. Dr. Laura Leal-Taixé
Learning a neural solver for multi-object tracking

15:40–
16:00
Yuesong Shen / Prof. Dr. Daniel Cremers
Deep learning: a non-alchemical view

16:00–
16:20
Vladimir Golkov, / Prof. Dr. Daniel Cremers
Equivariant Deep Learning

16:20–
16:40
Andrei Burov / Prof. Dr. Matthias Niessner
Learning to Optimize for Human Reconstructions


Track 2: Learning on Graphs and Networks & Representation Learning

14:20–
14:40
       Daniel Zügner / Prof. Dr. Stephan Günnemann
Robust deep learning on graphs

14:40–
15:00
Cornelius Fritz, Marc Schneble, Sevag Kevork / Prof. Dr. Göran Kauermann
Applied Network Science

15:00–
15:20
Max Berrendorf / Prof. Dr. Volker Tresp
Knowledge Graph Matching

15:20–
15:40
Alex Markham / Prof. Dr. Moritz Grosse-Wentrup
Measurement Dependence Inducing Latent Causal Models

15:40–
16:00
Nora Kassner / Prof. Dr. Hinrich Schütze
Negated and Misprimed Probes for Pretrained Language Models: Birds Can Talk, But Cannot Fly

16:00–
16:20
Mohammad Lotfollahi / Prof. Dr. Dr. Fabian Theis
Query to reference single-cell integration with transfer learning

16:20–
16:40
Marius Lange / Prof. Dr. Dr. Fabian Theis
Mapping the fate of single cells with RNA velocity using CellRank


Track 3: Automatic and Explainable Modeling & Computational Models for Large-Sclae ML

14:20–
14:40
       Dr. David Ruegamer / Prof. Dr. Bernd Bischl
Semi-Structured Deep Distributional Regression

14:40–
15:00
Julia Moosbauer, Martin Binder / Prof. Dr. Bernd Bischl
Multi-Objective Hyperparameter Tuning and Feature Selection using Filter Ensembles

15:00–
15:20
Theresa Ullmann, Christina Nießl / Prof. Dr. Anne-Laure Boulesteix
Cluster Analysis and Feature Rankings: Validation, benchmarking and over-optimism concerns

15:20–
15:40
Moritz Herrmann / PD Dr. Fabian Scheipl
Finding and evaluating embeddings for functional data

15:40–
16:00
Li Qian / Prof. Dr. Christian Böhm
Clustering Large-Scaled Datasets using Deep Learning

16:00–
16:20
Anna Beer / Prof. Dr. Peer Kröger
Evaluation of Results from Unsupervised Learning Processes

16:20–
16:40
Daniyal Kazempour / Prof. Dr. Thomas Seidl
Recent Advances in Correlation Clustering

16:40–
17:00
Sandra Obermeier / Prof. Dr. Thomas Seidl
Active Learning - Diversity vs. Uncertainty Sampling


17:00–
17:30
       Prof. Dr. Bernd Bischl
Closing Remarks

29.07.2020


Related

Link to MCML General Assembly

18.11.2024

MCML General Assembly

MCML General Assembly 2024 celebrated innovation and collaboration with inspiring talks, junior Flash Talks, and meaningful networking opportunities.


Link to LRZ Visit

24.10.2024

LRZ Visit

MCML visited Leibniz Rechenzentrum in Garching, exploring their supercomputer and GPU cluster during an insightful afternoon!


Link to MCML-Exhibition at Deutsches Museum

24.10.2024

MCML-Exhibition at Deutsches Museum

The MCML Exhibition at the Deutsches Museum showcased cutting-edge technology, captivating visitors during Munich's Long Night of Museums.


Link to The MCML at the All Hands Meeting 2024 in Dresden

23.10.2024

The MCML at the All Hands Meeting 2024 in Dresden

The MCML participated in the All Hands Meeting 2024 of the German AI Competence Centers from October 7-8.


Link to DSSGx Munich 2024 Closing Event

30.09.2024

DSSGx Munich 2024 Closing Event

The closing event of DSSGx Munich 2024 (Data Science for Social Good).