UNDERSTANDING CORTICAL NETWORKS RELATED TO SPEECH USING DEEP LEARNING ON ECOG DATA
OUR PAPER WAS PUBLISHED on ISBI 2020 as Best Paper Finalist LINK
OUR PAPER WAS PUBLISHED on ISBI 2020 as Best Paper Finalist LINK
Parts of this works difficulty is its steps and precision it requires. Since our exRNA-seq is different (it has less RNA reads), we have to explore the mapping sequence. We determine sequential mapping order, using peak calling because most long RNAs are fragments in blood. We also did matrix proces
We then turn to predict RNA motif (especially RNA-protein interaction related motif). It is another harder problem compared with simply applying deep neural network to 1D and 2D structure data. We develop the mixture model for PWM optimization. We explore the possibility to use VAE for unsupervise
For Synapse project, I work with Zudi and Donglai, we now rank No.1 in the CREMI contest. And we will submit a paper to CVPR this November.
We proposed a new mixed linear model Mixed Ridge with Fast cross validation to pick parameters. We also propose Metric Regressor for few shot learning.
We collaborate with Jun Li in New York University.
As a student from life science background with machine learning and deep learning skills, I have a broader mind to think about medical image problems from different views. From my perspectives, deep learning aided medical image analysis will soon have a wide range of application.
- SummerIntern/synapticpartner at master · james20141606/SummerIntern · GitHub - Synapse polarity - SummerIntern/synapsecluster at master · james20141606/SummerIntern · GitHub
- SummerIntern/synapticpartner at master · james20141606/SummerIntern · GitHub - Synapse polarity