Contact person
Olof Mogren
Senior Researcher
Contact Olof
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Learning machines seminars – previous seminars
Here you will find the previous seminars of 2023. Full archive can be found in the menu to the right.
2024
April
2024-04-11: Alouette van Hove, University of Oslo
Guiding drones by information gain
2024-04-04: Karsten Kreis, NVIDIA Toronto AI Lab (16:00)
Visual Generative AI with Diffusion Models – From Static Pixels to Video, 3D and 4D Synthesis
March
2024-03-28: Yonghao Xu, Linköping University
Machine learning for remote sensing
2024-03-21: Fredrik Gustafsson, Karolinska Institutet
How reliable is your regression model’s uncertainty under real-world distribution shifts?
2024-03-14: Santiago Martinez Balvanera, University College London
Data-driven bat monitoring: leveraging machine learning for effective solutions
February
2024-02-22: Alexander Mathis, EPFL
Measuring behavior and modeling the brain with machine learning
January
2024-01-25: Joakim Lindblad, Uppsala University
Trustworthy AI-based decision support in cancer diagnostics
2024-01-18: Serge Belongie, University of Copenhagen
Challenges in Fine-Grained Image Analysis
2023
December
2023-12-07: Stefan Bauer, TU Munich
Neural causal models
November
2023-11-30: Ben Weinstein, University of Florida
General Models for Airborne Wildlife Detection
2023-11-23: Alisa Devlic, Sony AI
Superhuman racing AI through deep reinforcement learning
2023-11-16: Jonas Hellgren, RISE
Reinforcement learning - theory and applications
2023-11-09: Nataša Sladoje, Uppsala University
Automated alignment of multimodal images: To (deep) learn – or not?
2023-11-02: Priya L. Donti, MIT and Climate Change AI
Optimization-in-the-loop ML for energy and climate
October
2023-10-19: Valentin De Bortoli, Google Deepmind
Diffusion Schrödinger Bridge Matching
2023-10-05: Klaus-Robert Müller, TU Berlin
Machine Learning and AI for the Sciences — Towards Understanding
September
2023-09-28: Johan Östman, AI Sweden
The reality of federated learning: from life sciences to finance and beyond
2023-09-21: Nico Lang, University of Copenhagen
Global vegetation monitoring with probabilistic deep learning
2023-09-14: Virginia Smith, CMU
Evaluating Large-Scale Learning Systems
2023-09-07: Adam Breitholtz, Chalmers University of Technology
Unsupervised domain adaptation by learning using privileged information
August
2023-08-31: Zahra Taghiyar Renan, Halmstad University
From domain adaptation to federated learning
May
2023-05-25: Puzhao Zhang, KTH
Remote Sensing for Wildfire using Deep Learning
2023-05-11: Jonathan Sauder, École polytechnique fédérale de Lausanne (EPFL)
Unsupervised 3D Mapping from Video
2023-05-04: Ida Arvidsson, Lund University
Applications of AI in Medical Image Analysis
April
2023-04-27: Pontus Stenetorp, University College London (UCL)
LLMs and Future of NLP
2023-04-20: Rico Sennrich, University of Zurich
Knowledge Transfer Across Languages and Modalities
2023-04-13: Elijah Cole, Caltech
Learning from real-world data
March
2023-03-23: Gabrielle Flood, Lund University
Motion Maps with Statistical Deformations
2023-03-16: Stefanos Georganos, Karlstad University/KTH
Filling the gaps: AI and Earth Observation
2023-03-09: Shay Cohen, University of Edinburgh
Summarization with Latent Structure, Context Factors and Quantitative Precision
February
2023-02-23: Alexander Ilin, Aalto University
Hierarchical Imitation Learning with Vector Quantized Models
2023-02-09: Joakim Nivre, Erik Ylipää, and Olof Mogren, RISE
ChatGPT and other large language models
2023-02-02: Vincent Szolnoky, Chalmers
Model Gradient Similarity
January
2023-01-26: Lena Voita, FAIR
Interpretability in NLP
2023-01-19: Giulia Fanti, Carnegie Mellon University
Communication Complexity of Federated Learning
2023-01-12: Mark D. Plumbley, University of Surrey: AI for Sound
AI for Sound
