ML in PL
About us: Founded based on the experiences in organizing of the ML in PL Conference (formerly PL in ML), the ML in PL Association is a non-profit organization devoted to fostering the machine learning community in Poland and promoting a deep understanding of ML methods. Even though ML in PL is based in Poland, it seeks to provide opportunities for international cooperation.
ML in PL 2024
Krzysztof Kotowski - Good Practices for Applied Computer Science | ML in PL 2024
Adam Karczmarz - On (Dynamic) Shortest Paths Data Structures | ML in PL 2024
Maciej Wołczyk - Adaptiveness in Deep Learning Models | ML in PL 2024
Przemysław Spurek - NeRF Based Generative Models | ML in PL 2024
Daniel Śliwiński & Patryk Radoń - Leveraging Feature Store for Recommendations | ML in PL 2024
Tom Rainforth - Modern Bayesian Experimental Design | ML in PL 2024
Omar Rivasplata - Meta-analysis of Bayesian Analyses | ML in PL 2024
Marcin Przewięźlikowski - Augmentation-Aware SSL with Conditioned Projector | ML in PL 2024
Tomasz Piotrowski - Fixed Points of Nonnegative Neural Networks | ML in PL 2024
Adam Dziedzic - Open LLMs are Necessary for Private Adaptations | ML in PL 2024
Adriana Borowa - Deep Learning for Effective Analysis of High Content Screening | ML in PL 2024
Marek Justyna - RNAgrail: Model for RNA 3D Structure Prediction | ML in PL 2024
Tomek Korbak - RLHF as conditioning on human preferences | ML in PL 2024
Wojciech Samek - Explainable AI for LLMs | ML in PL 2024
Dawid Rymarczyk - Current Trends in Intrinsically Interpretable Deep Learning | ML in PL 2024
Tudor Coman - Leveraging Multi-Armed Bandit Algorithms for Dynamic Decision Making | ML in PL 2024
Patryk Wielopolski - From Theory to Practice: A Journey with Knowledge Graphs | ML in PL 2024
Alicja Rączkowska - AlleNoise - classification benchmark with real-world label noise | ML in PL 2024
Bartłomiej Sobieski - Global Counterfactual Directions | ML in PL 2024
Tomasz Sapiński - Revolutionizing IT Operations with AI: The Comarch Experience | ML in PL 2024
Klaudia Balcer - Exceeding Historical Exposure in Session-Based Recommender Systems | ML in PL 2024
Jan Dubiński - CDI: Copyrighted Data Identification in Diffusion Models | ML in PL 2024
Adam Pardyl - AdaGlimpse: Active Visual Exploration w/ Arbitrary Glimpse Pos & Scale | ML in PL 2024
Franziska Boenisch - Finding NeMo: Memorization Neurons in Diffusion Models | ML in PL 2024
Maciej Chrabąszcz - Aggregated Attributions for Explaining 3D Segmentation Models | ML in PL 2024
Przemysław Spurek - Neural Rendering: The Future of 3D Modeling | ML in PL 2024
Kamil Deja - Personalisation of Large-Scale Diffusion Models | ML in PL 2024
Roberto Calandra - Perceiving, Understanding, and Interacting through Touch | ML in PL 2024
Bartłomiej Cupiał - Fine-tuning RL Models is a Forgetting Mitigation Problem | ML in PL 2024