We meet every Monday, at 10 AM in MI^2 DataLab (room 044, Faculty of Mathematics and Information Science, Warsaw University of Technology) or online.
Join us at https://meet.drwhy.ai.
Schedule for the first half of the semester (track: Context matters in Deep Learning Models - Computer Vision):
- 07.10 - guest lecture by nadkom. dr Paweł Olber
- 14.10 - Do Not Explain Vision Models without Context - Paulina Tomaszewska
- 21.10 - Positional Label for Self-Supervised Vision Transformer - Filip Kołodziejczyk
- 28.10 - Adversarial examples vs. context consistency defense for object detection - Hubert Baniecki
- 04.11 - Unlocking the Power of Spatial and Temporal Information in Medical Multimodal Pre-training - Bartosz Kochański
- 18.11 - User study: Visual Counterfactual Explanations for Improved Model Understanding - Bartek Sobieski
- 25.11 - Vision Transformers provably learn spatial structure - Vladimir Zaigrajew
- 02.12 - Null-text Inversion for Editing Real Images using Guided Diffusion Models - Dawid Płudowski
- 09.12 - Diffusion-Based Scene Graph to Image Generation with Masked Contrastive Pre-Training - Tymoteusz Kwieciński
- 20.01 - Connecting counterfactual and attributions modes of explanation - Jan Jakubik
- 19.02.2024 - PhD Thesis discussion Explanation methods for sequential data model
- 26.02.2024 - PhD Thesis discussion Modele rekomendacyjne wspólnej filtracji w serwisach ogłoszeniowych
- 04.02.2024 - PhD Thesis presentation Modele rekomendacyjne wspólnej filtracji w serwisach ogłoszeniowych
- 11.03.2024 - PhD Thesis discussion Analysis and texture recognition of digital images for computer aided skin lesions diagnostics
- 18.03.2024 - PhD Thesis presentation Analysis and texture recognition of digital images for computer aided skin lesions diagnostics
- 25.03.2024 - Law in AI - Andrzej Porębski
- 08.04.2024 - Introduction to counterfactual explanations track - Mateusz Krzyziński, Bartek Sobieski
- 15.04.2024 - The Privacy Issue of Counterfactual Explanations: Explanation Linkage Attacks - Mikołaj Spytek
- 22.04.2024 - Text-to-Image Models for Counterfactual Explanations: A Black-Box Approach - Tymoteusz Kwieciński
- 06.05.2024 - GLOBE-CE: A Translation Based Approach for Global Counterfactual Explanations - Piotr Wilczyński
- 13.05.2024 - Introduction to ViT and transformer attributions - Filip Kołodziejczyk
- 20.05.2024 - MI^2 PhD thesis presentations - Weronika Guzik, Katarzyna Kobylińska, Katarzyna Woźnica.
- 27.05.2024 - AtMan: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation - Maciej Chrabąszcz
- 03.06.2024 - Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet - Vladimir Zaigrajew
- 10.06.2024 - Semester summary and discussion.
- 09.10.2023 - Organizational matters - Hubert Baniecki, Maciej Chrabąszcz, Bartek Sobieski
- 16.10.2023 - On Minimizing the Impact of Dataset Shifts on Actionable Explanations - Hubert Baniecki
- 23.10.2023 - On the Robustness of Removal-Based Feature Attributions - Mateusz Krzyziński
- 30.10.2023 - Discussion - AdvXAI: Robustness of explanations
- 06.11.2023 - Representation Engineering - Maciej Chrabąszcz
- 13.11.2023 - Adaptive Testing of Computer Vision Models - Mikołaj Spytek
- 20.11.2023 - Red Teaming Language Models with Language Models - Piotr Wilczyński
- 27.11.2023 - Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned - Vladimir Zaigrajew
- 04.12.2023 - Discussion - RedTeaming of foundation models
- 11.12.2023 - Introduction to Diffusion Models - Bartek Sobieski
- 18.12.2023 - Glaze: Protecting artists from style mimicry by text-to-image model - Tymoteusz Kwieciński
- 08.01.2023 - FLIRT: Feedback Loop In-context Red Teaming - Hubert Ruczyński
- 15.01.2024 - Red-Teaming the Stable Diffusion Safety Filter - Mateusz Grzyb
- 22.01.2024 - Discussion - Diffusion models for XAI