NYU Deep Learning SP21 - 06L – Latent variable EBMs for structured prediction

Course website: http://bit.ly/DLSP21-web Playlist: http://bit.ly/DLSP21-YouTube Speaker: Yann LeCun Chapters 00:00:00 – Welcome to class 00:00:17 – Training of an EBM 00:04:27 – Contrastive vs. regularised / architectural methods 00:05:21 – General margin loss 00:09:34 – List of loss functions 00:13:45 – Generalised additive margin loss 00:17:53 – Joint embedding architectures 00:21:29 – Wav2Vec 2.0 00:27:14 – XLSR: multilingual speech recognition 00:29:16 – Generative adversarial networks (GANs) 00:37:24 – Mode collapse 00:41:45 – Non-contrastive methods 00:43:19 – BYOL: bootstrap your own latent 00:44:27 – SwAV 00:46:45 – Barlow twins 00:51:29 – SEER 00:54:29 – Latent variable models in practice 00:57:34 – DETR 01:01:21 – Structured prediction 01:04:53 – Factor graph 01:12:47 – Viterbi algorithm whiteboard time 01:30:24 – Graph transformer networks 01:46:48 – Graph composition, transducers 01:48:38 – Final remarks