corpus.blog
56,966 blogs · [ { "id": "01a0e76e-dfb7-70e4-8c8e-7939030a364a", "title": "Robots Must Be Ephemeralized", "url": "https://blog.evjang.com/2021/09/ephemeralization.html", "published_at": "2021-09-20T23:36:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-793903853c2a", "title": "ML Mentorship: Some Q/A about RL", "url": "https://blog.evjang.com/2021/07/rl-qa.html", "published_at": "2021-07-30T20:36:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-7939040f5ed5", "title": "Stonks are What You Can Get Away With: NFTs and Financial Nihilism", "url": "https://blog.evjang.com/2021/06/nft.html", "published_at": "2021-06-19T23:59:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-793904ae901e", "title": "Sovereign Arcade: Currency as High-Margin Infrastructure", "url": "https://blog.evjang.com/2021/05/arcade.html", "published_at": "2021-05-27T00:02:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-793904b7484c", "title": "Science and Engineering for Learning Robots", "url": "https://blog.evjang.com/2021/03/learning-robots.html", "published_at": "2021-03-14T21:30:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-793905a5ae92", "title": "Don't Mess with Backprop: Doubts about Biologically Plausible Deep Learning", "url": "https://blog.evjang.com/2021/02/backprop.html", "published_at": "2021-02-13T21:45:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-79390684128d", "title": "How to Understand ML Papers Quickly", "url": "https://blog.evjang.com/2021/01/understanding-ml.html", "published_at": "2021-01-26T05:39:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-793906da7bca", "title": "Software and Hardware for General Robots", "url": "https://blog.evjang.com/2020/11/moravec-bots.html", "published_at": "2020-11-29T07:53:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-7939070ea9dd", "title": "My Criteria for Reviewing Papers", "url": "https://blog.evjang.com/2020/09/reviewing.html", "published_at": "2020-09-27T18:27:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-79390712713f", "title": "Chaos and Randomness", "url": "https://blog.evjang.com/2020/09/chaos.html", "published_at": "2020-09-13T18:17:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-793907817a23", "title": "Free Office Hours for Non-Traditional ML Researchers", "url": "https://blog.evjang.com/2020/06/free-office-hours-for-non-traditional.html", "published_at": "2020-06-20T19:35:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-79390877c9a0", "title": "Three Questions that Keep Me Up at Night", "url": "https://blog.evjang.com/2020/04/three-questions-that-keep-me-up-at-night.html", "published_at": "2020-04-02T02:03:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-793908f8e9be", "title": "Selected Quotes from \"The Dark Ages of AI Panel Discussion\"", "url": "https://blog.evjang.com/2019/12/aaai84.html", "published_at": "2019-12-26T04:10:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-7939092c630c", "title": "Differentiable Path Tracing on the GPU/TPU", "url": "https://blog.evjang.com/2019/11/jaxpt.html", "published_at": "2019-11-29T05:50:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-793909d2f403", "title": "Robinhood, Leverage, and Lemonade", "url": "https://blog.evjang.com/2019/11/robinhood-leverage.html", "published_at": "2019-11-06T15:18:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-79390a8f56a7", "title": "Normalizing Flows in 100 Lines of JAX", "url": "https://blog.evjang.com/2019/07/nf-jax.html", "published_at": "2019-07-06T19:10:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-79390abd1a65", "title": "Tips for Training Likelihood Models", "url": "https://blog.evjang.com/2019/07/likelihood-model-tips.html", "published_at": "2019-07-05T20:04:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-79390b299e33", "title": "Lessons from AI Research Projects: The First 3 Years", "url": "https://blog.evjang.com/2019/05/ai-research-lessons.html", "published_at": "2019-05-24T00:32:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-79390b83dca4", "title": "Fun with Snapchat's Gender Swapping Filter", "url": "https://blog.evjang.com/2019/05/fun-with-snapchats-gender-swapping.html", "published_at": "2019-05-13T01:36:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-79390c641db8", "title": "What I Cannot Control, I Do not Understand", "url": "https://blog.evjang.com/2019/03/causal-rl.html", "published_at": "2019-03-10T22:10:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-79390d50f3d2", "title": "Meta-Learning in 50 Lines of JAX", "url": "https://blog.evjang.com/2019/02/maml-jax.html", "published_at": "2019-02-21T16:06:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-79390dc6564d", "title": "Thoughts on the BagNet Paper", "url": "https://blog.evjang.com/2019/02/bagnet.html", "published_at": "2019-02-06T07:35:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-79390e383995", "title": "Uncertainty: a Tutorial", "url": "https://blog.evjang.com/2018/12/uncertainty.html", "published_at": "2018-12-28T18:14:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-79390e3c3b75", "title": "Machine Learning Memes", "url": "https://blog.evjang.com/2018/11/memes.html", "published_at": "2018-12-01T05:42:00+00:00" }, { "id": "01a0e76e-dfb7-70e4-8c8e-79390ee4aa45", "title": "Dijkstra's in Disguise", "url": "https://blog.evjang.com/2018/08/dijkstras.html", "published_at": "2018-08-08T08:09:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d90a7a4dcd", "title": "Bots & Thoughts from ICRA2018", "url": "https://blog.evjang.com/2018/06/icra2018.html", "published_at": "2018-06-22T05:40:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d90a956f33", "title": "Aesthetically Pleasing Learning Rates", "url": "https://blog.evjang.com/2018/04/aesthetic-lr.html", "published_at": "2018-04-01T07:28:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d90b006d7d", "title": "Teacup", "url": "https://blog.evjang.com/2018/02/teacup-story.html", "published_at": "2018-02-23T21:41:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d90b8817bc", "title": "Doing a Concurrent Masters at Brown", "url": "https://blog.evjang.com/2018/01/brown-cm.html", "published_at": "2018-01-23T18:07:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d90b954713", "title": "机器学习中的表达能力, 训练难度和泛化性能", "url": "https://blog.evjang.com/2018/01/exp-train-gen-zh-hans.html", "published_at": "2018-01-19T16:38:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d90c7716e9", "title": "La expresividad, la entrenabilidad y la generalización en el aprendizaje automático", "url": "https://blog.evjang.com/2018/01/exp-train-gen-es.html", "published_at": "2018-01-19T16:02:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d90d6d7d68", "title": "Normalizing Flows Tutorial, Part 2: Modern Normalizing Flows", "url": "https://blog.evjang.com/2018/01/nf2.html", "published_at": "2018-01-17T23:30:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d90e202b38", "title": "Normalizing Flows Tutorial, Part 1: Distributions and Determinants", "url": "https://blog.evjang.com/2018/01/nf1.html", "published_at": "2018-01-17T23:30:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d90e6aa0ef", "title": "Gamma Correction", "url": "https://blog.evjang.com/2017/12/gamma-correction.html", "published_at": "2017-12-26T04:36:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d90f049188", "title": "Expressivity, Trainability, and Generalization in Machine Learning", "url": "https://blog.evjang.com/2017/11/exp-train-gen.html", "published_at": "2017-11-20T21:31:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d90fc81540", "title": "Summary of NIPS 2016", "url": "https://blog.evjang.com/2017/01/nips2016.html", "published_at": "2017-01-02T22:24:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d9107637a5", "title": "Tutorial: Categorical Variational Autoencoders using Gumbel-Softmax", "url": "https://blog.evjang.com/2016/11/tutorial-categorical-variational.html", "published_at": "2016-11-09T07:00:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d910c5a101", "title": "Riemann Summation and Physics Simulation are Statistically Biased", "url": "https://blog.evjang.com/2016/09/riemann-bias.html", "published_at": "2016-09-07T04:36:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d91175500d", "title": "Monte Carlo Variance Reduction Techniques in Julia", "url": "https://blog.evjang.com/2016/09/variance-reduction-part1.html", "published_at": "2016-09-06T00:32:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d911f04f45", "title": "A Beginner's Guide to Variational Methods: Mean-Field Approximation", "url": "https://blog.evjang.com/2016/08/variational-bayes.html", "published_at": "2016-08-08T06:50:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d91283eff4", "title": "Why Randomness is Important for Deep Learning", "url": "https://blog.evjang.com/2016/07/randomness-deep-learning.html", "published_at": "2016-07-25T06:56:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d913680879", "title": "What product breakthroughs will recent advances in deep learning enable?", "url": "https://blog.evjang.com/2016/07/what-product-breakthroughs-will-recent.html", "published_at": "2016-07-16T18:22:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d91388ee96", "title": "How to Get an Internship", "url": "https://blog.evjang.com/2016/07/how-to-get-internship.html", "published_at": "2016-07-11T13:34:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d9142e46b5", "title": "Adversarial Exploration Policies for Robust Model Learning", "url": "https://blog.evjang.com/2016/06/adversarial-exploration-policies-for.html", "published_at": "2016-06-25T12:44:00+00:00" }, { "id": "01a0e789-34ec-714d-9b89-26d914cd5476", "title": "Understanding and Implementing Deepmind's DRAW Model", "url": "https://blog.evjang.com/2016/06/understanding-and-implementing.html", "published_at": "2016-06-25T12:38:00+00:00" }, { "id": "01a0e789-34ed-7228-a083-131ea8bd351b", "title": "Generative Adversarial Nets in TensorFlow (Part I)", "url": "https://blog.evjang.com/2016/06/generative-adversarial-nets-in.html", "published_at": "2016-06-25T12:28:00+00:00" }, { "id": "01a0e789-34ed-7228-a083-131ea9471720", "title": "My Internship Experiences at Pixar, Google, and Two Sigma", "url": "https://blog.evjang.com/2016/06/my-internship-experiences-at-pixar.html", "published_at": "2016-06-25T12:20:00+00:00" } ] posts Claim your blog
Back to blog.evjang.com
Blog · corpus.blog/blogs/blog.evjang.com/posts

blog.evjang.com

blog.evjang.com

2021

Robots Must Be Ephemeralizedoriginal ↗
20 Sept 2021
ML Mentorship: Some Q/A about RLoriginal ↗
30 Jul 2021
Stonks are What You Can Get Away With: NFTs and Financial Nihilismoriginal ↗
19 Jun 2021
Sovereign Arcade: Currency as High-Margin Infrastructureoriginal ↗
27 May 2021
Science and Engineering for Learning Robotsoriginal ↗
14 Mar 2021
Don't Mess with Backprop: Doubts about Biologically Plausible Deep Learningoriginal ↗
13 Feb 2021
How to Understand ML Papers Quicklyoriginal ↗
26 Jan 2021

2020

Software and Hardware for General Robotsoriginal ↗
29 Nov 2020
My Criteria for Reviewing Papersoriginal ↗
27 Sept 2020
Chaos and Randomnessoriginal ↗
13 Sept 2020
Free Office Hours for Non-Traditional ML Researchersoriginal ↗
20 Jun 2020
Three Questions that Keep Me Up at Nightoriginal ↗
2 Apr 2020

2019

Selected Quotes from "The Dark Ages of AI Panel Discussion"original ↗
26 Dec 2019
Differentiable Path Tracing on the GPU/TPUoriginal ↗
29 Nov 2019
Robinhood, Leverage, and Lemonadeoriginal ↗
6 Nov 2019
Normalizing Flows in 100 Lines of JAXoriginal ↗
6 Jul 2019
Tips for Training Likelihood Modelsoriginal ↗
5 Jul 2019
Lessons from AI Research Projects: The First 3 Yearsoriginal ↗
24 May 2019
Fun with Snapchat's Gender Swapping Filteroriginal ↗
13 May 2019
What I Cannot Control, I Do not Understandoriginal ↗
10 Mar 2019
Meta-Learning in 50 Lines of JAXoriginal ↗
21 Feb 2019
Thoughts on the BagNet Paperoriginal ↗
6 Feb 2019

2018

Uncertainty: a Tutorialoriginal ↗
28 Dec 2018
Machine Learning Memesoriginal ↗
1 Dec 2018
Dijkstra's in Disguiseoriginal ↗
8 Aug 2018
Bots & Thoughts from ICRA2018original ↗
22 Jun 2018
Aesthetically Pleasing Learning Ratesoriginal ↗
1 Apr 2018
Teacuporiginal ↗
23 Feb 2018
Doing a Concurrent Masters at Brownoriginal ↗
23 Jan 2018
机器学习中的表达能力, 训练难度和泛化性能original ↗
19 Jan 2018
La expresividad, la entrenabilidad y la generalización en el aprendizaje automáticooriginal ↗
19 Jan 2018
Normalizing Flows Tutorial, Part 2: Modern Normalizing Flowsoriginal ↗
17 Jan 2018
Normalizing Flows Tutorial, Part 1: Distributions and Determinantsoriginal ↗
17 Jan 2018

2017

Gamma Correctionoriginal ↗
26 Dec 2017
Expressivity, Trainability, and Generalization in Machine Learningoriginal ↗
20 Nov 2017
Summary of NIPS 2016original ↗
2 Jan 2017

2016

Tutorial: Categorical Variational Autoencoders using Gumbel-Softmaxoriginal ↗
9 Nov 2016
Riemann Summation and Physics Simulation are Statistically Biasedoriginal ↗
7 Sept 2016
Monte Carlo Variance Reduction Techniques in Juliaoriginal ↗
6 Sept 2016
A Beginner's Guide to Variational Methods: Mean-Field Approximationoriginal ↗
8 Aug 2016
Why Randomness is Important for Deep Learningoriginal ↗
25 Jul 2016
What product breakthroughs will recent advances in deep learning enable?original ↗
16 Jul 2016
How to Get an Internshiporiginal ↗
11 Jul 2016
Adversarial Exploration Policies for Robust Model Learningoriginal ↗
25 Jun 2016
Understanding and Implementing Deepmind's DRAW Modeloriginal ↗
25 Jun 2016
Generative Adversarial Nets in TensorFlow (Part I)original ↗
25 Jun 2016
My Internship Experiences at Pixar, Google, and Two Sigmaoriginal ↗
25 Jun 2016