Achieving Data-Efficient Neural Networks with Hybrid Concept-based Models: Tobias Opsahl (UiO)
25:07
Anomaly Detection with Conditioned Denoising Diffusion Models: A. Mousakhan (University of Freiburg)
1:19:56
Building Neural Network Models That Can Reason
24:45
Towards Explainable AI 2.0 with Concept-based Explanations: Reduan Achtibat & Maxmilian Dreyer
1:02:55
Towards Practical and Efficient Neural Data Compression (Stephan Mandt, UC Irvine)
58:49
Deep learning for medical imaging applications
4:00:58
CVPR #18567 - Efficient Neural Networks: From Algorithm Design to Practical Mobile Deployment
30:34
FreqRISE: Explaining time series using frequency masking: Thea Brüsch (DTU Compute)
25:12