Marco Morik
Marco Morik
Doctoral Researcher
Marco Morik is a PhD Student in the Machine Learning Group at Technische Universität Berlin working on Uncertainty Estimation and Generative Models for Inverse Problems. He received his master degree in Computer Science from TU Berlin in 2019 with a focus on discrete optimization and Machine Learning. Since 2022 he is working in the Research Group Probabilistic Modeling and Inference with Dr. Shinichi Nakajima.
Best Paper Award SIGIR 2020
- Deep Generative Models
- Probabilistic Models
- Uncertainty Estimation
- Inverse Problems
Marco Morik, Laure Ciernik, Lukas Thede, Luca Eyring, Shinichi Nakajima, Zeynep Akata, Lukas Muttenthaler
Revealing Task-Dependent Layer Relevance via Attentive Multi-Layer Fusion
Sidney Bender, Marco Morik
Visual Disentangled Diffusion Autoencoders: Scalable Counterfactual Generation for Foundation Models
Laure Ciernik, Marco Morik, Lukas Thede, Luca Eyring, Shinichi Nakajima, Zeynep Akata, Lukas Muttenthaler
Beyond the final layer: Attentive multilayer fusion for vision transformers
Marco Morik, Ali Hashemi, Klaus-Robert Muller, Stefan Haufe, Shinichi Nakajima
Enhancing Brain Source Reconstruction by Initializing 3D Neural Networks with Physical Inverse Solutions
Laure Ciernik, Lorenz Linhardt, Marco Morik, Jonas Dippel, Simon Kornblith, Lukas Muttenthaler
Objective drives the consistency of representational similarity across datasets
BIFOLD researchers present three papers at ICLR 2024
The International Conference on Learning Representations (ICLR) is a Core-A gathering of experts who are dedicated to advancing a branch of artificial intelligence known as representation learning, which is also called deep learning.