Sameer Khurana (sameerkhurana10)

sameerkhurana10

Geek Repo

Company:MIT

Location:Cambridge

Home Page:http://people.csail.mit.edu/sameerk/

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Sameer Khurana's repositories

DSOL_rv0.2

deep protein solubility prediction

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pytorch-kaldi

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

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amdim-public

Public repo for Augmented Multiscale Deep InfoMax representation learning

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Autoregressive-Predictive-Coding

Autoregressive Predictive Coding: An unsupervised autoregressive model for speech representation learning

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DAVEnet-pytorch

Deep Audio-Visual Embedding network (DAVEnet) implementation in PyTorch

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DistSup

Representation learning for NLP @ JSALT19

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espnet

End-to-End Speech Processing Toolkit

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fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

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kaldi

This is now the official location of the Kaldi project.

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lnfmm

Latent Normalizing Flows for Many-to-Many Cross Domain Mappings (ICLR 2020)

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Montreal-Forced-Aligner

Command line utility for forced alignment using Kaldi

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nsf

Code for Neural Spline Flows paper

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parallel-wavenet-vocoder

A neural vocoder based on inverse autoregressive flow (IAF) used in parallel WaveNet

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pase

Problem Agnostic Speech Encoder

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probability

Probabilistic reasoning and statistical analysis in TensorFlow

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pytorch-vqvae

Vector Quantized VAEs - PyTorch Implementation

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ScalableFHVAE

This repository contains the code to reproduce the core results from the paper "Scalable Factorized Hierarchical Variational Autoencoders"

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SSDA_MME

Semi-supervised Domain Adaptation via Minimax Entropy

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tacotron

A TensorFlow implementation of Google's Tacotron speech synthesis with pre-trained model (unofficial)

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vae-lagging-encoder

PyTorch implementation of Lagging Inference Networks and Posterior Collapse in Variational Autoencoders

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WaveRNN

Pytorch implementation of Deepmind's WaveRNN model

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