3:20

Introduction to the Workshop [part 1]

MITCBMM

5:49

Introduction to the Workshop [part 2]

MITCBMM

43:29

Filters and Other Potions for Early Vision and Recognition

MITCBMM

32:41

Transformations in Early Vision from a Symmetry Argument

MITCBMM

9:33

Eulerian Video Magnification: Engineering Applications of a V1-like Image Representation

MITCBMM

11:10

Early Vision and Actions

MITCBMM

27:43

Panel Discussion: Early Features in Vision

MITCBMM

7:12

Frames and Gabor Wavelets

MITCBMM

50:37

Latent Structure Beyond Sparse Codes

MITCBMM

36:03

3+ Snippets on Learning Features: Material for Brainstorming

MITCBMM

31:37

Panel Discussion: Learning Features and Representations

MITCBMM

11:05

A Statistical Theory of Learning Data Representation

MITCBMM

8:32

Features and Representations

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12:45

Learning Data Representations: Hierarchies and Invariance

MITCBMM

52:16

Learning Invariant Feature Hierarchies

MITCBMM

32:08

Scattering Bricks to Build Invariants for Perception [part 1]

MITCBMM

27:10

Scattering Bricks to Build Invariants for Perception [part 2]

MITCBMM

52:21

M-theory

MITCBMM

10:38

Going After Object Recognition Performance to Discover How the Ventral Stream Works

MITCBMM

12:41

Learning Invariances and Hierarchies

MITCBMM

46:08

The Role of Mobility and Control in the Inference of Representations

MITCBMM

43:04

From Simple Innate Biases to Complex Visual Concepts

MITCBMM

50:56

Compositional Models: Complexity of Representation and Interference

MITCBMM

21:55

Panel Discussion: Beyond Feedforward Architectures

MITCBMM

13:32

What Makes a Good Representation? From Invariance to Causality

MITCBMM

10:20

Representation Learning

MITCBMM

3:01

Final Remarks

MITCBMM