Jan 17, 2024A Simple Creature Learning Generative Diffusion ModelPicture this: a creature exists that can only perceive images made up of a grand total of two pixels, each in one of sixteen glorious shades of gray. Despite what you might think, this creature is sophisticated. Not all two-pixel masterpieces are created equal in its eyes. It’s like us…Deep Learning7 min readDeep Learning7 min read

Jun 7, 2020Why Do Contigs Break in a Genome Assembly?Human Genome Reference Remains Incomplete When I was still a physics graduate student, I heard about the coolest thing at the time: we finished the Human Genome Project. It made me think about how awesome we can get all those little letters A/C/G and T in each of our cells. …7 min read7 min read

Nov 4, 2019Constructing A Graph for Genome Comparison SwiftlyIntroduction In recent years, a group of people in the scientific community starts to look into the application of graph to represent genomes. Graph is an extremely powerful abstraction for processing various kind of data. Meanwhile, mathematically, a graph is simple and complicated at the same time. To define a graph…Genomics8 min readGenomics8 min read

Published inTowards Data Science·Jan 20, 2019Deep Learning Approach for Separating Fast and Slow ComponentsSome Background (A slide deck for this work can be found https://speakerdeck.com/jchin/decomposing-dynamics-from-different-time-scale-for-time-lapse-image-sequences-with-a-deep-cnn) I left my job as a Scientific Fellow in PacBio after 9-year venture helping to make single-molecule sequencing becoming useful for the scientific community (see my story about the first couple year in PacBio there). Most of my technical/scientific work…Machine Learning6 min readMachine Learning6 min read

Mar 28, 2018DCNet — Denoising (DNA) Sequence With a LSTM-RNN and PyTorchCan we construct an error free consensus sequence from a set of noisy sequences using a neural network? (associated Jupyter notebooks can be found at https://github.com/cschin/DCNet) Using Neural Network to Remove Noise Using a deep convolutional neural network (CNN) for denoising images or constructing super resolution images has generating some quite amazing results. The basic idea…Machine Learning9 min readMachine Learning9 min read

Published inTowards Data Science·Jul 16, 2017Simple Convolutional Neural Network for Genomic Variant Calling with TensorFlowAI/Machine Learning in Biotech Startups No doubt that the fast development of recent progress using deep neural network has change the way that we can solve various problem from image recognition to genomics. Many startups (Viome/CZ Biohub/Deep Genomics) has emphasize using “AI/machine learning” for their research and product. Other relative “big” biotech startups in Silicon…Machine Learning10 min readMachine Learning10 min read

Mar 11, 2017From Boltzmann’s Atoms to “Knowledge Atoms”“In 1904 at a physics conference in St. Louis most physicists seemed to reject atoms and he was not even invited to the physics section.” — Wikipedia page about Ludwig Boltzmann Lucky for us, we live in an era that we can see “see” atoms with atomic force microscope. And…Physics5 min readPhysics5 min read

Published inIntuition Machine·Feb 28, 2017Some Thoughts about “Deep Unsupervised Learning using Nonequilibrium Thermodynamics”I have downloaded this paper “Deep Unsupervised Learning using Nonequilibrium Thermodynamics” for while but only read it through today. The typical example of direct connection between neural network and statistical physics is some spin-magnetic system like Ising model. This paper is interesting in the sense that it connected deep learning…Artificial Intelligence3 min readArtificial Intelligence3 min read

Feb 22, 2017E.T. Jaynes’ “Information Theory and Statistical Mechanics”“Information Theory and Statistical Mechanics” is the title of a paper that E.T. Jaynes published about 60 years ago. (Official journal link Information Theory and Statistical Mechanics, you can download PDF from https://journals.aps.org/pr/abstract/10.1103/PhysRev.106.620 ) For people who knows both information theory and statistical mechanics, one can recognize the same form…2 min read2 min read

Feb 18, 2017Statistical Physics and Machine LearningStatistical Physics and Machine Learning When I was young, I was attracted to physics for two things (1) elegant math that connects the abstract beauty and the physical world and (2) the possibility to explain complex behaviors in physics worlds starting from simple elements. …2 min read2 min read