diff --git a/src/components/HeroSection/index.jsx b/src/components/HeroSection/index.jsx index 8ca661e..581ffba 100755 --- a/src/components/HeroSection/index.jsx +++ b/src/components/HeroSection/index.jsx @@ -33,6 +33,94 @@ const citation = ` `; const news = [ +{ + date: "01/23/25", + content: ( + + Added{" "} + + bibfile + {" "} for book an + + LaTeX + {" "} + for equations + + ), +}, +{ + date: "12/17/24", + content: ( + + + + Video lectures + {" "} + for chapters 1-12 from Tamer Elsayed of Qatar University. + + ), +}, +{ + date: "12/05/24", + content: ( + + New{" "} + + blog + {" "} + on Neural network Gaussian processes + + ), +}, + + { + date: "11/14/24", + content: ( + + New{" "} + + blog + {" "} + on Bayesian Neural Networks + + ), + }, + { + date: "08/13/24", + content: ( + + New{" "} + + blog + {" "} + on Bayesian machine learning (function perspective) + + ), + }, + { + date: "08/05/24", + content: ( + + Added{" "} + + interactive figures + {" "} + to explore 1D linear regression, shallow and deep networks, Gabor model. + + ), + }, + { + date: "07/30/24", + content: ( + + New{" "} + + blog + {" "} + on Bayesian machine learning (parameter perspective) + + ), + }, { date: "05/22/24", content: ( @@ -184,10 +272,10 @@ export default function HeroSection() { Book Cover - - Download full PDF (27 May 2024) + + Download full PDF (21 November 2024) -
+
Errata - - +

+ ); diff --git a/src/components/Instructors/index.jsx b/src/components/Instructors/index.jsx index ee377d4..1856399 100644 --- a/src/components/Instructors/index.jsx +++ b/src/components/Instructors/index.jsx @@ -280,6 +280,12 @@ export default function InstructorsSection() { {" "} with MIT Press for answer booklet. + Interactive figures + + Interactive figures {" "} + to illustrate ideas in class + + Full slides Slides for 20 lecture undergraduate deep learning course: @@ -296,6 +302,11 @@ export default function InstructorsSection() { ))} + LaTeX for equations + A {" "} + working Latex file {" "} + containing all of the equations + Figures @@ -325,6 +336,11 @@ export default function InstructorsSection() { {" "} for editing equations in figures. + LaTeX Bibfile + The {" "} + bibfile {" "} + containing all of the references + diff --git a/src/components/Media/index.jsx b/src/components/Media/index.jsx old mode 100644 new mode 100755 index caf2d41..45f8a76 --- a/src/components/Media/index.jsx +++ b/src/components/Media/index.jsx @@ -120,23 +120,18 @@ export default function MediaSection() { by Vishal V.
  • - Amazon{" "} - - reviews - -
    • -
  • - Goodreads{" "} - - reviews{" "} - + Book{" "} + + review + {" "} + by Nidhin Chandrasekharan
  • Book{" "} - + review {" "} - by Vishal V. + by Justin Skycak
    • @@ -155,6 +150,10 @@ export default function MediaSection() { ))} + Video lectures + + Video lectures + {" "} for chapter 1-12 from Tamer Elsayed diff --git a/src/components/More/index.jsx b/src/components/More/index.jsx old mode 100644 new mode 100755 index ce2d2ea..8d76e80 --- a/src/components/More/index.jsx +++ b/src/components/More/index.jsx @@ -376,6 +376,51 @@ const aiTheory = [ "NTK and generalizability", ], }, + { + text: "Bayesian ML I", + link: "https://www.borealisai.com/research-blogs/bayesian-machine-learning-parameter-space/", + details: [ + "Maximum likelihood", + "Maximum a posteriori", + "The Bayesian approach", + "Example: 1D linear regression", + "Practical concerns", + ], + }, + { + text: "Bayesian ML II", + link: "https://www.borealisai.com/research-blogs/bayesian-machine-learning-function-space/", + details: [ + "Function space", + "Gaussian processes", + "Inference", + "Non-linear regression", + "Kernels and the kernel trick", + ], + }, + { + text: "Bayesian neural networks", + link: "https://rbcborealis.com/research-blogs/bayesian-neural-networks/", + details: [ + "Sampling vs. variational approximation", + "MCMC methods", + "SWAG and MultiSWAG", + "Bayes by backprop", + "Monte Carlo dropout", + ], + }, + { + text: "Neural network Gaussian processes", + link: "https://rbcborealis.com/research-blogs/neural-network-gaussian-processes/", + details: [ + "Shallow networks as GPs", + "Neural network Gaussian processes", + "NNGP Kernel", + "Kernel regression", + "Network stability", + ], + }, + ]; const unsupervisedLearning = [ @@ -689,7 +734,7 @@ export default function MoreSection() { - Book + Computer vision book {book.map((item, index) => (
  • @@ -817,7 +862,7 @@ export default function MoreSection() { - AI Theory + ML Theory {aiTheory.map((item, index) => (