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Causal Representation Learning
Mar 12, 2021
34 videos
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40:13
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (Paper Explained)
Yannic Kilcher
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1:31:00
Yoshua Bengio: Towards Causal Representation Learning
Brady Neal - Causal Inference
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51:34
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
RAIL
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33:46
Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning
Yannic Kilcher
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1:04:30
GPT-3: Language Models are Few-Shot Learners (Paper Explained)
Yannic Kilcher
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26:22
Representation Learning: A Review and New Perspectives
AISTATS 2014
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4:53
[CVPR 2020 Award Nominee] Momentum Contrast for Unsupervised Visual Representation Learning
ComputerVisionFoundation Videos
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27:45
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations
Yannic Kilcher
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4:32
Human-level concept learning through probabilistic program induction | Brendan Lake
Popular Mechanics
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30:11
Object-Centric Learning with Slot Attention
Computer Vision Seminar
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5:34
Shaping Belief States with Generative Environment Models for RL
Consistent Belief State
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9:11
Semi-Supervised Learning, Causality and the Conditional Cluster Assumption
Uncertainty in Artificial Intelligence
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38:18
A Simple Framework for Contrastive Learning of Visual Representations
Fellowship
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1:08
An Analysis of the Adaptation Speed of Causal Models
Montreal AI Symposium
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43:11
Learning Independent Causal Mechanisms
Steven Van Vaerenbergh
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7:57
Hidden Markov Nonlinear ICA: Unsupervised Learning from Nonstationary Time Series
Uncertainty in Artificial Intelligence
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28:21
Building Machines That Learn and Think Like People
MITCBMM
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10:50
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach
Amir-Hossein Karimi
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5:55
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms
Heng Ee, Angus
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19:11
Counterfactual Fairness
Microsoft Research
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1:01
Self-Supervised Learning of Video-Induced Visual Invariances
ComputerVisionFoundation Videos
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3:53
Discovering Causal Signals in Images
ComputerVisionFoundation Videos
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3:45
Revisiting Unreasonable Effectiveness of Data in Deep Learning Era
ComputerVisionFoundation Videos
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2:51
Solving Rubik's Cube with a Robot Hand
OpenAI
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2:01
A Compositional Object-Based Approach to Learning Physical Dynamics
Michael Chang
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4:54
CLEVRER: CoLlision Events for Video REpresentation and Reasoning
IBM Research
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9:08
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
Julian Schrittwieser
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1:22
Learning to Simulate Complex Physics with Graph Networks
Tobias Pfaff
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3:55
Flexible Neural Representation for Physics Prediction
Physics Prediction
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1:14
Action-Conditional Video Prediction using Deep Networks in Atari Games
Junhyuk Oh
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18:58
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
Steven Van Vaerenbergh
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2:30
Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects
Adam Kosiorek
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16:25
The Predictron: End-To-End Learning and Planning
TechTalksTV
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4:55
Latent-space Physics: Towards Learning the Temporal Evolution of Fluid Flow
Nils Thuerey
