Speaker: Sergey Nikolenko (St. Petersburg Department of Steklov Mathematical Institute of RAS)
Zoom ID: 849 3673 9875 Password: 123456
Beijing Time: 15:00-17:00 (Moscow Time: 10:00-12:00)
Schedule:
Date |
Topics |
Nov. 20 |
Attention in neural networks. Self-attention and the Transformer architecture. BERT and GPT families. |
Nov. 22 |
Variational autoencoders: idea and derivation. |
Nov. 25 |
Discrete latent spaces: VQ-VAE. VAE + Transformer = DALL-E. |
Nov. 27 |
Vision Transformers. Multimodal latent spaces: CLIP and BLIP, our recent work (LAPCA). |
Nov. 29 |
Case study: video retrieval. How it has developed in the last years. Postprocessing in video retrieval and our recent work (Sinkhorn transformations). |
Dec. 1 |
Topological data analysis: extracting features with topology. Our recent work (TDA for HuBERT, TDA for artificial text detection). |
Biography:
Sergey Nikolenko is a computer scientist specializing in machine learning and analysis of algorithms. He is the Head of AI at Synthesis AI, a San Francisco based company specializing on the generation and use of synthetic data for modern machine learning models, and also serves as the Head of the Artificial Intelligence Lab at the Steklov Mathematical Institute at St. Petersburg, Russia. Dr. Nikolenko's interests include synthetic data in machine learning, deep learning models for natural language processing, image manipulation, and computer vision, and algorithms for networking. His previous research includes works on cryptography, theoretical computer science, and algebra.