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99### Spring semester
1010
11- * 24.02
12- * 03.03 - Introduction to Sparse Autoencoders (ReLU, TopK, Anthropic Works) - (Vladimir)
13- * 10.03 - New and Related Work in SAE - (Vladimir)
14- * 17.03 - New and Related Work in SAE (additional time) - ( Vladimir)
15- * 24.03 - Interpreting CLIP with Hierarchical Sparse Autoencoders - Vladimir Zaigrajew
16- * 31.03 - PIP-Net - (advising Hubert )
17- * 07.04 - ProtoViT - ( advising Hubert )
11+ * 24.02 - Introduction to Sparse Autoencoders (ReLU, TopK, Anthropic Works) - (Vladimir)
12+ * 03.03 - New and Related Work in SAE - (Vladimir)
13+ * 10.03 - New and Related Work in SAE (additional time) - (Vladimir)
14+ * 17.03 - Interpreting CLIP with Hierarchical Sparse Autoencoders - Vladimir Zaigrajew
15+ * 24.03 - INTRO + PIP-Net: Patch-based intuitive prototypes for interpretable image classification (CVPR 2023) - (advising HB)
16+ * 31.03 - Interpretability benchmark for evaluating spatial misalignment of prototypical parts explanations (AAAI 2024) - (advising HB )
17+ * 07.04 - ProtoViT: Interpretable image classification with adaptive prototype-based vision transformers (NeurIPS 2024) - ( advising HB )
1818* 14.04 - Adversarial analysis of intrinsically interpretable deep learning - Hubert Baniecki
1919* 28.04 - Vlad
2020* 12.05 - Bartek
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