The ELTE Machine Learning Seminars are set up to explore a selection of intriguing topics in the realm of machine learning and complex systems. With sessions led by various members of our community, we aim to delve deep into subjects ranging from autoregressive models to the intricacies of interpretability. Each session promises an insightful discussion on the respective topic, enhanced by shared resources and in-depth presentations. Join us as we navigate through these captivating themes and push the boundaries of our understanding in the ML sphere.
Webpage: https://csabaibio.github.io/elte_ml_journal_club
Date: Thursdays from 11.45 to 13:00.
Location: ELTE Lágymányosi Campus, Pázmány Péter sétány 1/A, 5th floor, room 5.128.
Online meeting link: https://meet.google.com/fvd-soiu-ent
| Topic | Speaker/s | Date | Slides | Extra resources |
|---|---|---|---|---|
| Multimodal deep learning in oncology | Oz Kilim (ELTE) | 2024.02.01. | https://docs.google.com/presentation/d/1makXpCl7Y6XwJbPyFTCbbknV7aGnQWnZYIvWRaUQiaA/edit?usp=sharing | - |
| Retrieval Augmented Generation (RAG) - advanced solutions to improve the performance of Generative AI chatbots | Zoltan Fóris (Lynx Analytics) | 2024.02.15. | - | - |
| Michael Faran (DeepVoice/TAU) | 2024.02.29. | A quantiative framework to describe self- assembly based on trend-changepoints | - | |
| Dylan Behr (UCL) | 2024.03.14. | - | - |