CS-E407513 - Special Course in Machine Learning, Data Science and Artificial Intelligence D: Seminar on Deep Learning 2022, Lectures, 6.9.2022-29.11.2022

Topic outline

• Seminar schedule
  Session 1 (06.09) Audio
  

  • It’s Raw! Audio Generation with State-Space Models
    presenter: Teodors Kerimovs
    opponent:
  • Style Transfer of Audio Effects with Differentiable Signal Processing
    presenter: Otto Mikkonen
    opponent:

  Session 2 (13.09) Architectures/generalization/insights
  

  • Why do tree-based models still outperform deep learning on tabular data?
    presenter: Hiroshi Doyu
    opponent: Yaroslav Getman
  • Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets
    presenter: Aayush Kucheria
    opponent: Bernard Spiegl

  Session 3 (20.09) Architectures/generalization/insights
  

  • Predicting Out-of-Domain Generalization with Local Manifold Smoothness
    presenter: Jesse Hamalainen
    opponent: Bryn Louise
  • Epistemic Neural Networks
    presenter: Aleksi Maunu
    opponent: Eloi Moliner

  Session 4 (27.09) Audio
  

  • Guided-TTS: A Diffusion Model for Text-to-Speech via Classifier Guidance
    presenter: Antoni Jankowski
    opponent: Alexandru Dumitrescu
  • NU-Wave 2: A General Neural Audio Upsampling Model for Various Sampling Rates
    presenter: Eloi Moliner
    opponent: Daniel Carter

  Session 5 (04.10) Generative models
  

  • Structured Denoising Diffusion Models in Discrete State Spaces
    presenter: Alexandru Dumitrescu
    opponent: Antoni Jankowski
  • High-Resolution Image Synthesis with Latent Diffusion Models
    presenter: Hyunkyung Choo
    opponent: My Linh Nguyen

  Session 6 (11.10) Language grounding / Graph neural networks
  

  • Flamingo: a Visual Language Model for Few-Shot Learning
    presenter: My Linh Nguyen
    opponent: Christian Montecchiani
  • Pure Transformers are Powerful Graph Learners
    presenter: Maxim Smirnov
    opponent: Hiroshi Doyu

  Session 7 (25.10) Self-supervised learning
  

  • data2vec: A General Framework for Self-Supervised Learning in Speech; Vision and Language
    presenter: Yaroslav Getman
    opponent: Jesse Hamalainen
  • Masked Siamese Networks for Label-Efficient Learning
    presenter: Katja Voskoboinik
    opponent: Aleksi Maunu

  Session 8 (01.11) Graph neural networks
  

  • Equivariant Diffusion for Molecule Generation in 3D
    presenter: Severi Rissanen
    opponent: Riccardo Mereu
  • Constraint-based graph network simulator
    presenter: Bryn Louise
    opponent: Katja Voskoboinik

  Session 9 (08.11) Generative models / Audio
  

  • Label-Efficient Semantic Segmentation with Diffusion Models
    presenter: Hua Huang
    opponent: Aayush Kucheria
  • Chunked Autoregressive GAN for Conditional Waveform Synthesis
    presenter: Filip Zawadka
    opponent: Hyunkyung Choo

  Session 10 (15.11) AGI / Reasoning/compositionality
  

  • Gato: A Generalist Agent
    presenter: Bernard Spiegl
    opponent: Anton Naumov
  • Learning Iterative Reasoning through Energy Minimization
    presenter: Riccardo Mereu
    opponent: Maximilian Krahn

  Session 11 (22.11) RL
  

  • Offline RL Policies Should Be Trained to be Adaptive
    presenter: Christian Montecchiani
    opponent: Filip Zawadka
  • Decision Transformer: Reinforcement Learning via Sequence Modeling
    presenter: Daniel Carter
    opponent: Hua Huang

  Session 12 (29.11) RL
  

  • BYOL-Explore: Exploration by Bootstrapped Prediction
    presenter: Anton Naumov
    opponent: Maxim Smirnov
  • Transformers are Sample Efficient World Models
    presenter: Maximilian Krahn
    opponent: Severi Rissanen