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CS-E4070 - Special Course in Machine Learning and Data Science D: Seminar on Deep Learning 2020, 10.09.2020-03.12.2020

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Syllabus

Seminar schedule

  • Seminar schedule

    Seminar schedule

    Session 1 (10.09)
    • Representation Learning with Contrastive Predictive Coding
      presenter: Sebastian Szyller
      opponent: Khamal Dhakal
    • Large scale adversarial representation learning
      presenter: Paavo Reinikka
      opponent: Peter Lövei

    Session 2 (17.09)
    • A Simple Framework for Contrastive Learning of Visual Representations and Big Self-Supervised Models are Strong Semi-Supervised Learners
      presenter: Oliver Struckmeier
      opponent: Oliver Järnefelt
    • Generative Pretraining from Pixels
      presenter: Aleksi Maunu
      opponent: Yaroslav Getman

    Session 3 (24.09)
    • Reformer: The Efficient Transformer
      presenter: Sam Splisbury
      opponent: Onur Poyraz
    • Improving the Gating Mechanism of Recurrent Neural Networks
      presenter: Jesse Miettinen
      opponent: Andrey Sukhobok

    Session 4 (1.10)
    • Network Deconvolution
      presenter: Markus Ylisiurunen
      opponent: Katsiaryna Haitsiukevich
    • NVAE: A Deep Hierarchical Variational Autoencoder
      presenter: Trung Trinh
      opponent: Sebastian Szyller

    Session 5 (8.10)
    • Progressive learning and disentanglement of hierarchical representations
      presenter: Pashupati Hedge
      opponent: Paavo Reinikka
    • Weakly-Supervised Disentanglement Without Compromises
      presenter: Alex Hämäläinen
      opponent: Anirudh Jain

    Session 6 (15.10)
    • Improving Generative Imagination in Object-Centric World Models
      presenter: Maxim Afteniy
      opponent: Alex Hämäläinen
    • Causal Discovery in Physical Systems from Videos
      presenter: Sanna Hyvönen
      opponent: Trung Trinh

    Session 7 (29.10)
    • Discovering Symbolic Models from Deep Learning with Inductive Biases
      presenter: Anirudh Jain
      opponent: Sam Splibury
    • Learning to Simulate Complex Physics with Graph Networks
      presenter: Onur Poyraz
      opponent: Mohsen Amidzade

    Session 8 (5.11)
    • Text as Neural Operator: Image Manipulation by Text Instruction
      presenter: Andrey Sukhobok
      opponent: Aleksi Maunu
    • vq-wav2vec: Self-Supervised Learning of Discrete Speech Representations
      presenter: Yaroslav Getman
      opponent: Sebastian de Peuter

    Session 9 (12.11)
    • Deep Learning for Symbolic Mathematics
      presenter: Daniel Hopkins
      opponent: Pashupati Hedge
    • Neural Arithmetic Units
      presenter: Oliver Järnefelt
      opponent: Sanna Hyvönen

    Session 10 (19.11)
    • Concept Learners for Generalizable Few-Shot Learning
      presenter: Pius Ladendurber
      opponent: Daniel Hopkins
    • CURL: Contrastive Unsupervised Representations for Reinforcement Learning
      presenter: Katsiaryna Haitsiukevich
      opponent: Maxim Afteniy

    Session 11 (26.11)
    • What Can Learned Intrinsic Rewards Capture?
      presenter: Peter Lövei
      opponent: Pius Ladenburger
    • A distributional view on multi-objective policy optimization
      presenter: Mohsen Amidzade
      opponent: Oliver Struckmeier

    Session 12 (3.12)
    • Ready Policy One: World Building Through Active Learning
      presenter: Sebastiaan de Peuter
      opponent: Jesse Miettinen
    • Empirically Verifying Hypotheses Using Reinforcement Learning
      presenter: Kamal Dhakal
      opponent: Markus Ylisiurunen

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    • CS-E4070 - Special Course in Machine Learning and Data Science D: Seminar on Deep Learning 2020, 10.09.2020-03.12.2020
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      • – Instructions for report writing (CHEM)
      • School of Electrical Engineering (ELEC)
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    • CORONAVIRUS INFO
      • Koronavirus - tietoa opiskelijalle
      • Coronavirus - information for students
      • Coronavirus - information för studerande
      • Koronaviruksen vaikutus opiskeluun: kysymyksiä ja vastauksia
      • Effects of the coronavirus on studies: questions and answers
      • Coronaviruset och studierna: frågor och svar
      • Corona help for teachers
    • Service Links
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      • - Digital tools for teaching
      • - Personal data protection instructions for teachers
      • - Instructions for Students
      • - Workspace for thesis supervision
      • WebOodi
      • Into portal for students
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      • - Imagoa / Open science and images
      • IT Services
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    • ALLWELL?
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      • Starting Point of Wellbeing
      • About AllWell? study well-being questionnaire
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