Weekly research seminar at the Centre for Credible AI (CCAI)

We meet every Monday, at 10 AM in room 5.04 at Rektorska 4, Warsaw University of Technology - or online.

Join us at https://meet.drwhy.ai.

Year 2025/2026

Spring semester

• 23.02 - From local explanations to comprehensive mechanistic understanding of deep vision models - invited lecture by Maximilian Dreyer
• 02.03 - Challenges in Bayesian Neural Networks: Balancing Priors and Learning Biases - invited lecture by Tomasz Kuśmierczyk
• 09.03 - Short Cycles for Local Density and Community Detection - invited lecture by Ryan DeWolfe
• 16.03 - Higher Order Attention - special session by Tomasz Steifer
• 23.03 - Machine learning supervised neurotherapy - special session by Jacek Rogala
• 30.03 - CCAI PHYS-XAI leader introduction - special session by Julek Sienkiewicz
• 06.04 - No seminar - spring break
• 13.04 - Olympiad-level formal mathematical reasoning with reinforcement learning - Bartosz Naskręcki
• 20.04 - Attribution-Guided Decoding - Vladimir Zaigrajew
• 11.05 - Flow and Diffusion models + Terrain Diffusion - Jakub Grzywaczewski
• 18.05 - Semantic Vector Spaces as Scientific Instruments: Measuring Meaning with the Supervised Semantic Differential - invited lecture by Hubert Plisiecki
• 25.05 - Shifting the Gradient: Understanding How Defensive Training Methods Protect Language Model Integrity - Jan Piotrowski
• 01.06 - From Debate to Equilibrium: Belief‑Driven Multi‑Agent LLM Reasoning via Bayesian Nash Equilibrium - Inez Okulska
• 08.06 - From Memorization to Reasoning in the Spectrum of Loss Curvature - Teodor Lamort de Gail
• 15.06 - From End-to-end to Step-by-step: Learning to Abstract via Abductive Reinforcement Learning - Maciej Świechowski
• 22.06 - invited lecture by Yashar Moshfeghi
• 29.06 - Selective Generation for Controllable Language Models - Herbert Potrykus
• 13.07 - Game-Theoretic Consensus Deep Learning for Adaptive Flood Prediction in Digital Twin Environments - invited lecture by Michał Godziszewski
• 20.07 - Maciej Szymkowski
• 27.07 - Tomasz Steifer
• 3.08 - invited lecture by Maximilian Muschalik
• 10.08 - Michał Włodarczyk
• 17.08 - Kamil Książek
• 24.08 - Piotr Suszyński
• 31.08 - Paweł Gelar
• 7.09 - (Activation Oracles: Training and Evaluating LLMs as General-Purpose Activation Explainers)[https://github.com/MI2DataLab/MI2DataLab_Seminarium/tree/master/2026/2026_09_07_activation_oracles] - Vladimir Zaigrajew
• 14.09 - Julian Sienkiewicz
• 21.09 - Damian Wójtowicz
• 28.09 - Jakub Grzywaczewski
• 5.10 - Agata Wijata
• 12.10 - Inez Okulska
• 19.10 - Surprise!
• 26.10 - Bartłomiej Sobieski

Fall semester

Schedule

• 06.10 - organizational meeting
• 13.10 - Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models - Bartosz Kochański
• 20.10 - What Has a Foundation Model Found? Using Inductive Bias to Probe for World Models - Michał Włodarczyk
• 27.10 - Monthly sync meeting (Hubert Baniecki, Dawid Płudowski, Julian Sienkiewicz)
• 03.11 - ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features - Jakub Grzywaczewski
• 17.11 - Counterfactual Explanations on Robust Perceptual Geodesics - Bartek Sobieski
• 24.11 - Monthly sync meeting (Paulina Tomaszewska, Paweł Struski, Vladimir Zaigrajew)
• 01.12 - ImageNet-trained CNNs are not biased towards texture: Revisiting feature reliance through controlled suppression - Dawid Płudowski
• 08.12 - Attention (as Discrete-Time Markov) Chains - Kamil Książek
• 15.12 - Monthly sync meeting (Bartek Sobieski, Jakub Grzywaczewski, Michał Włodarczyk)
• 12.01 - Emergent Misalignment: Controlling Persona Drift with Vectors and Inoculation - Jan Piotrowski
• 19.01 - Monthly sync meeting (Kamil Książek, Bartosz Kochański, Agata Kaczmarek)
• 19.01 - Retro meeting

Invited lectures

• 09.02 - LLMs learn surprising things - Jan Betley and Anna Sztyber-Betley
• 16.02 - Detection of machine generated texts – data sets, methods and a stylometric viewpoint - Jeremi Ochab

Year 2024/2025

Spring semester

• 24.02 - Tracking information flow in biosystems from high-throughput data - Miron Kursa
• 03.03 - Introduction to Sparse Autoencoders SAE with ReLU (Anthropic; Blog; 21.05.2024), TopK (OpenAI; ICLR 2025; 06.06.2025) and JumpReLU (DeepMind; 09.08.2024; EMNLP 2024 Workshop) - (advising Vladimir)
• 10.03 - Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models (Northeastern University; ICLR 2025; 31.03.2025) - (advising Vladimir)
• 17.03 - Sparse Autoencoders Do Not Find Canonical Units of Analysis (Durham University/Independent; ICLR 2025; 07.02.2025) - (advising Vladimir)
• 24.03 - Interpreting CLIP with Hierarchical Sparse Autoencoders (My paper; Under Review; 30.01.2025) - Vladimir Zaigrajew
• 31.03 - ProtoViT: Interpretable image classification with adaptive prototype-based vision transformers - Paweł Gelar
• 07.04 - PIP-Net: Patch-based intuitive prototypes for interpretable image classification - Karol Dobiczek
• 14.04 - Birds look like cars: Adversarial analysis of intrinsically interpretable deep learning - Hubert Baniecki
• 28.04 - Vlad (ICLR)
• 05.05 - Explaining in Diffusion: Explaining a Classifier Through Hierarchical Semantics with Text-to-Image Diffusion Models - Jakub Świstak
• 12.05 - Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model - Jakub Grzywaczewski
• 19.05 - Diffusion Posterior Sampling for General Noisy Inverse Problems - Tymoteusz Kwieciński
• 26.05 - DiG-IN: Diffusion Guidance for Investigating Networks -- Uncovering Classifier Differences Neuron Visualisations and Visual Counterfactual Explanations - Dawid Płudowski
• 31.05 - Wyjazd zespołu do Wilgi
• 02.06
• 09.06

Fall semester

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
• 16.12 - Rethinking Visual Counterfactual Explanations Through Region Constraint - Bartek Sobieski
• 13.01 - Controlling The World by Sleight of Hand - Jakub Świstak
• 20.01 - Connecting counterfactual and attributions modes of explanation - Jan Jakubik

Year 2023/2024

Summer semester

Schedule

• 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.

Winter semester

Schedule

• 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

Year 2022/2023

Spring semester

Schedule

• 2023-02-20 - set-up meeting
• 2023-02-27 - Acquisition of chess knowledge in AlphaZero - Bartek Sobieski, Mikołaj Spytek
• 2023-03-06 - Aggregation of explanations - Weronika Hryniewska, Przemysław Biecek
• 2023-03-13 - Ensembles of models - how to get the most benefits - Anna Kozak, Hubert Ruczyński
• 2023-03-20 - Unfooling Perturbation-Based Post Hoc Explainers - Hubert Baniecki, Mateusz Krzyziński
• 2023-03-27 - Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application to Credit-Risk Evaluation - Mikołaj Spytek, Mateusz Krzyziński
• 2023-04-03 - From "Where" to "What": Towards Human-Understandable Explanations through Concept Relevance Propagation - Maciej Chrabąszcz, Bartek Sobieski
• 2023-04-17 - Explainable Artificial Intelligence for the Study of the Impact of Environmental Factors on Human Health- Donato Romano (guest, remote meeting)
• 2023-04-24 - Shapley values and functional decompositions - Mateusz Krzyziński, Hubert Baniecki
• 2023-05-08 - Scalable Gaussian process-based transfer surrogates for hyperparameter optimization - Mateusz Grzyb, Katarzyna Woźnica
• 2023-05-15 - Automated Benchmark-Driven Design and Explanation of Hyperparameter Optimizers - Hubert Ruczyński, Anna Kozak
• 2023-05-22 - Formal methods for neural networks verification - Paulina Tomaszewska,
• 2023-05-29 - Adaptive Testing and Debugging of NLP models - Emilia Wiśnios, Maciej Chrabąszcz
• 2023-06-05 - Meta-learning from Tasks with Heterogeneous Attribute Spaces - Katarzyna Woźnica
• 2023-06-12 - summary meeting

Fall semester

Overview phase

• 2022-10-03 - Organisation of the seminar
• 2022-10-10 - xLungs - Efficient and Explainable Diagnostics’ Support for Radiologists
• 2022-10-17 - HOMER - Achieving Responsible ML by Human Oriented autoMated machinE leaRning
• 2022-10-24 - ATLAS - Automated documenT anaLysis for sociAl awareneSs

Research phase

• 2022-11-07 - Explainable machine learning for survival analysis - Mateusz Krzyziński, Mikołaj Spytek, Hubert Baniecki

• 2022-11-14 - Lungs vector representations - Maciej Chrabąszcz, Bartek Sobieski, Weronika Hryniewska-Guzik

• 2022-11-21 - ATLAS: Explaining abstractive summarization - Emilia Wiśnios

• 2022-11-28 - How to organize our work - discussion

  
  

• 2022-12-05 - Cancelled

• 2022-11-12 - New era of AutoML? - Katarzyna Woźnica, Anna Kozak

• 2022-11-19 - research presentation: xLungs

  
  

Update phase

• 2023-01-02 - HOMER update
• 2023-01-09 - ATLAS update
• 2023-01-16 - Workshop: How to prepare presentation with storytelling? - Zuzanna Kwiatkowska
• 2023-01-23 - Summary
  

Year 2021/2022

Spring semester

• 2022-06-13 Summary of the seminar and ongoing matters
• 2022-06-06 LIMEcraft: Handcrafted superpixel selection and inspection for Visual eXplanations - Weronika Hryniewska
• 2022-05-30 Industrial PhD (lesson learned) - Tomasz Stanisławek
• 2022-05-23 Hyperparameter optimization with Reinforcement Learning - Bartek Sobieski
• 2022-05-16 Monitoring of AI regulations using natural language processing - Stanisław Giziński & Stanisław Łaniewski
• 2022-05-09 Extensions of the SHAP method: using Shapley value to interpret models with dependencies and survival analysis models - Mateusz Krzyziński
• 2022-04-25 Comparative analysis of veins and arteries used in coronary artery bypass grafting. PhD Thesis - Piotr Zawierucha
• 2022-04-11 Monitoring of AI regulations using natural language processing - Stanisław Giziński
• 2022-04-04 🎉 PhD defense (11-14 am) - Tomasz Stanisławek
• 2022-03-28 Running services and calculations in our Kubernetes cluster - Piotr Piątyszek
• 2022-03-21 Hybrid model of Fuzzy Cognitive Map - Decision Tree in making medical decisions - Hoang Thien Ly
• 2022-03-14 Duel-based Deep Learning system for solving IQ tests - Paulina Tomaszewska
• 2022-03-07 Expected goal (xG) models and XAI - Mustafa Cavus
• 2022-02-28 Organisation of the seminar and ongoing matters

Fall semester

• 2022-01-31 Impact of Imperfect Diagnostic Tests in ME/CFS Association Analyses - João Malato
• 2022-01-24 Models selecting prototypes with ProtoPNet - Adam Kozłowski
• 2022-01-17 Bayesian Optimization with a Prior for the Optimum - Bartłomiej Sobieski
• 2022-01-10 Evaluating explanations - Hubert Baniecki
• 2022-01-03 Explanations of multimodal neural networks - Piotr Czarnecki
• 2021-12-20 NeurIPS2021 – takeaways - Paulina Tomaszewska
• 2021-12-13 Auto-sklearn:Automating Design Decisions in AutoML - Mustafa Cavus
• 2021-12-06 Malaria pipelines - Andre Fonseca
• 2021-11-29 Auto-sklearn: Portfolio Successive Halving in PoSH - Mustafa Cavus
• 2021-11-22 MONAI framework for deep learning in healthcare imaging - Michał Sokólski
• 2021-11-15 Multi-fidelity optimization - Kasia Woźnica
• 2021-11-08 Stream data analysis - Kamil Wereszczyński
• 2021-10-25 Auto-sklearn: problem statement + challenge description - Kasia Woźnica
• 2021-10-18 How to increase the visibility of a statistician in the modern world of collaborative research? - Nuno Sepúlveda
• 2021-10-11 Multivariate data vis, Linear projections, and their application to local explanations of models - Nicholas Spyrison
• 2021-10-04 Organisation of the seminar

Rok 2020/2021

Semestr letni

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MI2 Summer CONF August 2, 2021 - Conference Book

SUCCESSful data visualization using International Business Communication Standard - Bartosz Sawicki, Kinga Ułasik

triplot4python: the remedy for dealing with correlated features in explanations - Mateusz Krzyziński , Artur Żółkowski

The medLIME algorithm - Adrianna Grudzień

Multitasking and transfer learning capabilities in Deep Learning - Maria Kałuska

Guide through jungle of models! forester: An R package to automatically select between tree-based models - Hoang Thien Ly, Szymon Szmajdziński

FairPANs - bringing fairness to neural networks - Hubert Ruczyński

metaMIMIC: an analysis of hyperparameter transfer possibilities for tabular data using MIMIC-IV database - Mateusz Grzyb , Zuzanna Trafas

Monitoring of AI regulation - Stanisław Giziński

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Wakacyjny Klub Dyskusyjny, czwartki o 10:00

• 2021-08-26
  • Sickest-first policy & Predictive Models for Liver Transplant Candidates in the US - Hoang Thien Ly
• 2021-08-12
  • NeurIPS 2021 Datasets and Benchmarks Track - Tomasz Stanisławek
  • The Lean Startup - Maria Kałuska
• 2021-08-05
  • A brief introduction to object detection - Jakub Wiśniewski
  • The use of denoising autoencoders for categorical and continuous variables - Anna Kozak
• 2021-07-29
  • Shapley Flow: A Graph-based Approach to Interpreting Model Predictions - Mateusz Krzyziński
  • Hackathons - Zuzanna Trafas
• 2021-07-22
  • DVC (Data Version Control) - Stanisław Giziński
  • Metaheuristic optimization - Mateusz Grzyb
• 2021-07-15
  • i-Algebra: Towards Interactive Interpretability of Deep Neural Networks - Hubert Baniecki
  • CVPR - Weronika Hryniewska

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• 2021-06-17 MI2 responsible AI talks - An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department - Farah Shamout & DeCoviD team at 1 p.m.
• 2021-06-14 Podsumowanie roku
• 2021-06-07 What Will You Tell Me About the Chart? - Recognition and Description Process - Karolina Seweryn, Katarzyna Lorenc
• 2021-05-31 Robustness in Computer Vision - Sebastian Cygert
• 2021-05-24 Protagonists’ Catcher in Novels - A Dataset and A Tool - Weronika Łajewska
• 2021-05-19 Cross-validation: what does it estimate and how well does it do it? - Alicja Gosiewska
• 2021-05-17 The deriving of a computational approach test for testing equality of several populations’ means in the presence of nuisance parameter - Mustafa Cauvus
• 2021-05-10 Monitor wariantów SARS-CoV-2 - Hubert Baniecki, Piotr Piątyszek, Hanna Zdulska
• 2021-04-26 Towards Explainable AutoML: xAutoML - Marius Lindauer
• 2021-04-19 MI2DataLab against Covid19
• 2021-04-12 Generative Adversarial Network in Medical Imaging - Weronika Hryniewska
• 2021-03-29 Marginal Attribution by Conditioning on Quantiles - Anna Kozak
• 2021-03-22 Beyond Fairness: Towards a Just, Equitable, and Accountable Computer Vision - Piotr Czarnecki
• 2021-03-15 Discussion on reviewing conference papers
• 2021-03-08 MIMIC III - Medical Information Mart for Intensive Care - Katarzyna Kobylińska
• 2021-03-01 Cleora - Barbara Rychalska
• 2021-02-22 Gonito & Information extraction challenges and their evaluation - Filip Graliński

Semestr zimowy

• 2021-01-25 Seminarium organizacyjne
• 2021-01-18 Transfer Learning of pre-trained CNN representations - Michał Sokólski
• 2021-01-11 Adversarial attacks on Explainable AI methods - Hubert Baniecki, Wojciech Kretowicz
• 2020-12-21 Podsumowanie roku 2020
• 2020-12-14 Towards explainable meta-learning - Kasia Woźnica
• 2020-12-07 Responsible AI & H2O - Jean-Matthieu SCHERTZER
• 2020-11-30 XAI for image based COVID-19 detection - Weronika Hryniewska
• 2020-11-23 Looking to listen: Audio separation and localization with visual clues - Piotr Czarnecki
• 2020-11-16 Interpretable Machine Learning with application to Credit Scoring - Alicja Gosiewska
• 2020-11-09 XAI in medicine - Katarzyna Kobylińska
• 2020-11-02 Graph-based Recommendation Systems - Barbara Rychalska
• 2020-10-26 2020 NLP trends & UniCase - Rethinking Casing in Language Models - Tomasz Stanisławek
• 2020-10-19
  • Arena - the universal dashboard for models exploration & Telemetry - API for collecting anonymized data from DrWhy.AI tools - Piotr Piątyszek
  • fairmodels - flexible tool for bias detection, visualization, and mitigation - Jakub Wiśniewski
• 2020-10-12
  • Autumn update - Hubert Baniecki
  • Landscape of R packages for eXplainable Artificial Intelligence - Szymon Maksymiuk
• 2020-10-05 Seminarium organizacyjne

Rok 2019/2020

Semestr letni

• 2020-09-11 Semantyczne modelowanie danych doświadczalnych i jego zastosowanie w analizie wyników fenotypowania roślin - Hanna Ćwiek-Kupczyńska
• 2020-08-03 Review of chest imaging findings in COVID-19 - Weronika Hryniewska
• 2020-07-28 Introduction to fairness - basic concepts and implementation of fairmodels package - Jakub Wiśniewski
• 2020-06-08 XAI for modelling of covid-19 mortality for the Polish population - Przemysław Biecek
• 2020-06-01 Detecting and overcoming bias in data with explainable artificial intelligence - Agnieszka Mikołajczyk
• 2020-05-25 Graph Convolutional Networks - Piotr Czarnecki
• 2020-05-18
  • Hyperparameter importance - Kasia Woźnica
  • Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior - Dominika Basaj
• 2020-05-11
  • Benchmart dla NLP ERASER - Alicja Gosiewska
  • Weight Poisoning Attacks on Pre-trained Models - Tomasz Stanisławek
• 2020-05-04
  • Pathologist-Level Grading of Prostate Biopsies with Artificial Intelligence - Weronika Hryniewska
• 2020-04-27
  • Learning Disentangled Representations for Recommendation - Barbara Rychalska
  • AI dla raka płuc - Katarzyna Kobylińska
• 2020-04-06 Visualizing and Measuring the Geometry of BERT - Dominika Basaj
• 2020-03-30 The Mythos of Model Interpretability - Kasia Woźnica, Anna Kozak
• 2020-03-23 AI Explainability 360 by IBM - Michał Kuźba
• 2020-03-09 NLP: Current trends in language modelling and transfer learning - Tomasz Stanisławek
• 2020-03-02 Lifting Interpretability-Performance Trade-off via Automated Feature Engineering (SAFE) - Alicja Gosiewska
• 2020-02-24 Wyjaśnienia sieci ARA - Weronika Hryniewska

Semestr zimowy

• 2020-01-27
  • flashlight czyli prześwietlanie czarnych skrzynek - Alicja Gosiewska
  • Wyjaśnialny ML w naukach medycznych - Kasia Kobylińska
• 2020-01-20
  • The World of Decisions - Stanisław Łaniewski
  • ACL, ICONIP - Barbara Rychalska, Dominika Basaj
• 2020-01-13 ARA: accurate, reliable and active histopathological image classification framework with Bayesian deep learning - Łukasz Rączkowski
• 2019-12-16 Podsumowanie roku
• 2019-12-09 How can we discover a biomarker for Chronic Fatigue Syndrome? - Nuno Sepúlveda
• 2019-12-02
  • Multiple Defaults - Kasia Woźnica
  • Internships - Michał Kuźba
• 2019-11-25 Neural Machine Translation: achievements, challenges and the way forward - Barbara Rychalska
• 2019-11-18 CONLL & EMNLP - Tomasz Stanisławek
• 2019-10-28 Inpainting - Weronika Hryniewska
• 2019-10-21 Analiza dźwięku - Piotr Czarnecki
• 2019-10-07
  • Elo - Kasia Woźnica
  • Funnel plot - Szymon Maksymiuk
• 2019-09-30 Seminarium organizacyjne

Rok 2018/2019

Semestr letni

• 2019-06-10 - Podsumowanie roku
• 2019-06-03 - Analiza danych marketingowych - Adrian Foltyn
• 2019-05-27 - Adversarial training on text datasets - Kamil Grabowski
• 2019-05-20 - Mini-hackaton dot. wizualizacji modeli
• 2019-05-13 - Mikrosegmentacja - Adam Dobrakowski
• 2019-05-06 - Przyczynowość - Mateusz Kobos
• 2019-04-29 - Optymalizacja bayesowska - Michał Burdukiewicz
• 2019-04-15 - Tunability: Importance of Hyperparameters of Machine Learning Algorithms - Alicja Gosiewska
• 2019-04-08 - Feast - Przemysław Biecek
• 2019-04-01 - Named Entity Recognition - is there a glass ceiling? - Tomasz Stanisławek
• 2019-03-25 - Artykuł na ACL - Dominika Basaj i Alicja Gosiewska.
• 2019-03-18 - ExplainPrediction & sales example - Mateusz Staniak
• 2019-03-11 - TFML - Michał Kuźba
• 2019-03-04 - Explaining Classifications for Individual Instances - Katarzyna Kobylińska
• 2019-02-25 - Bioinformatyka - Michał Burdukiewicz
• 2019-02-18 - Seminarium organizacyjne

Semestr zimowy

• 2019-01-28 - Przegląd prac z konferencji FATML - Dominika Basaj
• 2019-01-21 - Wizualna eksploracja modeli - Agnieszka Ciepielewska
• 2019-01-14 - NA - Alicja Gosiewska
• 2019-01-07 - Propensity Weighting to Investigate Health Disparities and Assess Indirect Effects - Chris Drake, UC Davis
• 2018-12-10 - Przewidywanie właściwości sekwencji biologicznych w oparciu o analizę n-gramów - Michał Burdukiewicz
• 2018-12-03 - Wrażenia z Krakowa - Alicja Gosiewska, Mateusz Staniak
• 2018-11-26 - EMNLP Conference Highlights - Dominika Basaj
• 2018-11-19 - Atencja - Tomasz Stanisławek
• 2018-11-12 - Wolne (100-lecie dnia po odzyskaniu niepodległości)
• 2018-11-5, 2018-11-6 - Christoph Molnar (LMU), Alicja Gosiewska, Przemysław Biecek, Klasyfikacja tekstów z użyciem Transfer Learning i Active Learning - Michał Kuźba (seminarium robocze)
• 2018-10-29 - Mythos of Interpretability - Mateusz Staniak
• 2018-10-22 - The Family of Relief algorithms - Alicja Gosiewska
• 2018-10-15 - Concept drift & IML - Mateusz Staniak, Przemyslaw Biecek
• 2018-10-8 - Interpretability & Security in NLP models - Dominika Basaj

Rok 2017/2018

• Git, GitHub
• Prezentacje naukowe
• Cheatsheety
• Czysty kod
• pkgdown
• Travis
• Web service