new NKT tutorial
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Simon Prince
@@ -23,18 +23,28 @@ const HeroSection = () => {
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<HeroNewsTitle>RECENT NEWS:</HeroNewsTitle>
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<HeroNewsItem>
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<HeroNewsItemDate>03/12/24</HeroNewsItemDate>
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<HeroNewsItemContent> Book now available again.</HeroNewsItemContent>
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<HeroNewsItemDate>05/22/24</HeroNewsItemDate>
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<HeroNewsItemContent> New <UDLLink href="https://www.borealisai.com/research-blogs/neural-tangent-kernel-applications/"> blog </UDLLink> about the applications of the neural tangent kernel.</HeroNewsItemContent>
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</HeroNewsItem>
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<HeroNewsItem>
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<HeroNewsItemDate>02/21/24</HeroNewsItemDate>
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<HeroNewsItemContent>New blog about the <UDLLink href="https://www.borealisai.com/research-blogs/the-neural-tangent-kernel/">Neural Tangent Kernel.</UDLLink></HeroNewsItemContent>
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<HeroNewsItemDate>05/10/24</HeroNewsItemDate>
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<HeroNewsItemContent> Positive <UDLLink href="https://github.com/udlbook/udlbook/blob/main/public/NMI_Review.pdf">review</UDLLink> in Nature Machine Intelligence.</HeroNewsItemContent>
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</HeroNewsItem>
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{/* <HeroNewsItem>
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<HeroNewsItemDate>03/12/24</HeroNewsItemDate>
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<HeroNewsItemContent> Book now available again.</HeroNewsItemContent>
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</HeroNewsItem> */}
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<HeroNewsItem>
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<HeroNewsItemDate>02/21/24</HeroNewsItemDate>
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<HeroNewsItemContent>New blog about the <UDLLink href="https://www.borealisai.com/research-blogs/the-neural-tangent-kernel/">Neural Tangent Kernel</UDLLink>.</HeroNewsItemContent>
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</HeroNewsItem>
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{/* <HeroNewsItem>
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<HeroNewsItemDate>02/15/24</HeroNewsItemDate>
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<HeroNewsItemContent> First printing of book has sold out in most places. Second printing available mid-March.</HeroNewsItemContent>
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</HeroNewsItem>
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</HeroNewsItem> */}
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<HeroNewsItem>
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@@ -54,7 +64,7 @@ const HeroSection = () => {
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<HeroNewsItem>
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<HeroNewsItemDate>12/06/23</HeroNewsItemDate>
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<HeroNewsItemContent> I did an <UDLLink href="https://www.borealisai.com/news/understanding-deep-learning/">interview</UDLLink> discussing the book with Borealis AI.</HeroNewsItemContent>
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<HeroNewsItemContent> <UDLLink href="https://www.borealisai.com/news/understanding-deep-learning/">Interview</UDLLink> with Borealis AI.</HeroNewsItemContent>
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</HeroNewsItem>
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<HeroNewsItem>
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@@ -79,7 +89,7 @@ const HeroSection = () => {
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<HeroImgWrap>
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<Img src={img} alt="book cover"/>
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</HeroImgWrap>
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<HeroLink href="https://github.com/udlbook/udlbook/releases/download/v2.05/UnderstandingDeepLearning_04_18_24_C.pdf">Download full pdf (18 Apr 2024)</HeroLink>
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<HeroLink href="https://github.com/udlbook/udlbook/releases/download/v4.0.1/UnderstandingDeepLearning_05_27_24_C.pdf">Download full pdf (27 May 2024)</HeroLink>
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<HeroDownloadsImg src="https://img.shields.io/github/downloads/udlbook/udlbook/total" alt="download stats shield"/>
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<HeroLink href="https://mitpress.mit.edu/9780262048644/understanding-deep-learning/">Buy the book</HeroLink>
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<HeroLink href="https://github.com/udlbook/udlbook/raw/main/UDL_Answer_Booklet_Students.pdf">Answers to selected questions</HeroLink>
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@@ -64,6 +64,7 @@ const MediaSection = () => {
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<TopLine>Reviews</TopLine>
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<MediaContent>
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<ul>
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<li> Nature Machine Intelligence <MediaLink href="https://github.com/udlbook/udlbook/blob/main/public/NMI_Review.pdf"> review </MediaLink> by <MediaLink href="https://wang-axis.github.io/">Ge Wang</MediaLink></li>
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<li> Amazon <MediaLink href="https://www.amazon.com/Understanding-Deep-Learning-Simon-Prince-ebook/product-reviews/B0BXKH8XY6/">reviews</MediaLink></li>
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<li>Goodreads <MediaLink href="https://www.goodreads.com/book/show/123239819-understanding-deep-learning?">reviews </MediaLink></li>
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<li>Book <MediaLink href="https://medium.com/@vishalvignesh/udl-book-review-the-new-deep-learning-textbook-youll-want-to-finish-69e1557b018d">review</MediaLink> by Vishal V.</li>
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@@ -285,19 +285,22 @@ const MoreSection = () => {
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</MoreInnerP>
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</li>
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</MoreOuterList>
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<TopLine>Temporal models</TopLine>
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<MoreOuterList>
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<li>
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<MoreLink href="https://www.borealisai.com/en/blog/tutorial-11-sat-solvers-iii-factor-graphs-and-smt-solvers/" target="_blank" rel="noreferrer">SAT Solvers III</MoreLink>
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<MoreLink href="https://drive.google.com/file/d/1rrzGNyZDjXQ3_9ZqCGDmRMM3GYtHSBvj/view?usp=sharing" target="_blank" rel="noreferrer">Temporal models</MoreLink>
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<MoreInnerP>
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<MoreInnerList>
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<li> Satisfiability vs. problem size </li>
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<li> Factor graph representation </li>
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<li> Max product / sum product for SAT </li>
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<li> Survey propagation </li>
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<li> SAT with non-binary variables </li>
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<li> SMT solvers </li>
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<li> Kalman filter </li>
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<li> Smoothing </li>
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<li> Extended Kalman filter </li>
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<li> Unscented Kalman filter </li>
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<li> Particle filtering </li>
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</MoreInnerList>
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</MoreInnerP>
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</li>
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</MoreOuterList>
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<TopLine>Computer vision</TopLine>
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<MoreOuterList>
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@@ -400,28 +403,27 @@ const MoreSection = () => {
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<li> Training dynamics </li>
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<li> Empirical NTK for shallow network</li>
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<li> Analytical NTK for shallow network </li>
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<li> Empirical NTK for ddep network </li>
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<li> Empirical NTK for deep network </li>
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<li> Analtical NTK for deep network</li>
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</MoreInnerList>
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</MoreInnerP>
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</li>
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<li>
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<MoreLink href="https://www.borealisai.com/research-blogs/neural-tangent-kernel-applications/" target="_blank" rel="noreferrer">NTK applications</MoreLink>
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<MoreInnerP>
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<MoreInnerList>
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<li> Trainability </li>
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<li> Convergence bounds </li>
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<li> Evolution of parameters</li>
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<li> Evolution of predictions </li>
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<li> NTK Gaussian processes</li>
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<li> NTK and generalizability</li>
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</MoreInnerList>
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</MoreInnerP>
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</li>
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</MoreOuterList>
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<TopLine>Temporal models</TopLine>
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<MoreOuterList>
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<li>
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<MoreLink href="https://drive.google.com/file/d/1rrzGNyZDjXQ3_9ZqCGDmRMM3GYtHSBvj/view?usp=sharing" target="_blank" rel="noreferrer">Temporal models</MoreLink>
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<MoreInnerP>
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<MoreInnerList>
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<li> Kalman filter </li>
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<li> Smoothing </li>
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<li> Extended Kalman filter </li>
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<li> Unscented Kalman filter </li>
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<li> Particle filtering </li>
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</MoreInnerList>
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</MoreInnerP>
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</li>
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</MoreOuterList>
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<TopLine> Unsupervised learning</TopLine>
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<MoreOuterList>
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