Transformer models: an introduction and catalog A super concise and brief overview of almost all popular Transformer models. Written well and provide pointers for recent advances in Transformer model architectures. https://
arxiv.org/abs/2302.07730
@jeande_d
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Transformer Models: Introduction and Comprehensive Catalog Overview
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Mathematics of Diffusion Models: Deep Dive Resource
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On the Mathematics of Diffusion Models A great resource for those who want to dive deep into mathematics of diffusion models, the kind of models that revolutionized image generation. https://
arxiv.org/abs/2301.11108 -
Survey on Efficient Training Methods for Transformer Architectures
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A Survey on Efficient Training of Transformers Transformers are the one architecture driving AI research in most modalities. They require large compute resources, but more and more efficient training approaches are being proposed. A survey on the topic: https://
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Vision Transformers: Next Video on Visual Recognition Systems
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The next video will be about Vision Transformers. (Vision) Transformers are an integral part of current large-scale visual recognition systems and have made it easy to build multimodal systems, language and vision in particular. Working on it slowly, but surely.
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First Long Video on Transformers Receives 6K Views
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Very much surprised by the number of people who watched my video on Transformer and attention is all you need paper. ~6K views is a tangible indicator of how valuable video contents are given this was my first long video. Will do more of them!!
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Appreciation for FAIR Works in AI Research Tools and Vision
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Appreciate FAIR works in AI research tools and vision.
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Advanced Natural Language Processing USC Class Notes and Resources
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Advanced Natural Language Processing – University of Southern California – CLASS NOTES Comprehensive notes on various topics in machine learning and natural language processing: concepts, techniques, and algorithms. https://
elanmarkowitz.github.io/USC-CS662/asse
ts/files/class_notes.pdf
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Comprehensive Mathematical Foundations for Computer Science and Machine Learning
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Algebra, Topology, Differential Calculus, and Optimization Theory For Computer Science and Machine Learning – Jean Gallier, UPenn A comprehensive book that covers math theories related to CS and machine learning. Very intense, 2163 pages!!! Get a copy: https://
cis.upenn.edu/~jean/math-dee
p.pdf
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Survey on Transformers Applications in Reinforcement Learning
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A Survey on Transformers in Reinforcement Learning Transformers have been the prime mover of almost all modalities, from vision, speech, text and are showing potential applications in RL. This survey paper provides a nice taxonomy of Transformers in RL. https://
arxiv.org/abs/2301.03044 -
Deep Learning and Computational Physics Lecture Notes Shared
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(It's always nice to see people that condense a huge topic like DL into ~80 pages document and share it with the community) Deep Learning and Computational Physics – Lecture Notes: https://
arxiv.org/abs/2301.00942
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