AsmitaBhat30

airfoil-opt-gan

Experiment code associated with our paper: "Aerodynamic Design Optimization and Shape Exploration using Generative Adversarial Networks"

AsmitaBhat30

beta-tcvae

code for "Isolating Sources of Disentanglement in Variational Autoencoders".

Beta-VAE

Pytorch implementation of β-VAE

bezier-gan

Bézier Generative Adversarial Networks

CP-VAE

On Variational Learning of Controllable Representations for Text without Supervision https://arxiv.org/abs/1905.11975

DeepSDF

Learning Continuous Signed Distance Functions for Shape Representation

Dynamic-Dashboard-for-Covid-19-Data-Analysis

Dynamic dashboard - which can be updated by one click - of COVID-19 data with filtered and calculated data sets

lxmert

PyTorch code for EMNLP 2019 paper "LXMERT: Learning Cross-Modality Encoder Representations from Transformers".

Sentiment-Analysis-using-RNN-LSTM

AsmitaBhat30/lxmert

PyTorch code for EMNLP 2019 paper "LXMERT: Learning Cross-Modality Encoder Representations from Transformers".

AsmitaBhat30/airfoil-opt-gan

Experiment code associated with our paper: "Aerodynamic Design Optimization and Shape Exploration using Generative Adversarial Networks"

AsmitaBhat30/AsmitaBhat30

AsmitaBhat30/beta-tcvae

code for "Isolating Sources of Disentanglement in Variational Autoencoders".

AsmitaBhat30/Beta-VAE

Pytorch implementation of β-VAE

AsmitaBhat30/bezier-gan

Bézier Generative Adversarial Networks

AsmitaBhat30/CP-VAE

On Variational Learning of Controllable Representations for Text without Supervision https://arxiv.org/abs/1905.11975

AsmitaBhat30/DeepSDF

Learning Continuous Signed Distance Functions for Shape Representation

AsmitaBhat30/Dynamic-Dashboard-for-Covid-19-Data-Analysis

Dynamic dashboard - which can be updated by one click - of COVID-19 data with filtered and calculated data sets

AsmitaBhat30/Sentiment-Analysis-using-RNN-LSTM

AsmitaBhat30/Data-Augmentation-For-Wearable-Sensor-Data

A sample code of data augmentation methods for wearable sensor data (time-series data)

AsmitaBhat30/datasharing

The Leek group guide to data sharing

AsmitaBhat30/Deep-Learning-for-Aerodynamic-Prediction

This repository contains code used to create and train a deep neural network that replicates a RANS solver for aerodynamic prediction over airfoils.

AsmitaBhat30/DiffuseVAE

A combination of VAE's and Diffusion Models for efficient, controllable and high-fidelity generation from low-dimensional latents

AsmitaBhat30/Diffusion-Models

AsmitaBhat30/GAN_stability

Code for paper "Which Training Methods for GANs do actually Converge? (ICML 2018)"

AsmitaBhat30/iaf-vae

Pytorch Implementation of OpenAI's "Improved Variational Inference with Inverse Autoregressive Flow"

AsmitaBhat30/idgan

Official PyTorch implementation on ID-GAN: High-Fidelity Synthesis with Disentangled Representation by Lee et al., 2020.

AsmitaBhat30/Image-Synthesis-using-Conditional-GANs

AsmitaBhat30/inference-suboptimality

Code for "Inference Suboptimality in Variational Autoencoders"

AsmitaBhat30/MixNMatch

Pytorch implementation of MixNMatch

AsmitaBhat30/MNIST_Fashion_Classification

AsmitaBhat30/NVAE

The Official PyTorch Implementation of "NVAE: A Deep Hierarchical Variational Autoencoder" (NeurIPS 2020 spotlight paper)

AsmitaBhat30/sigma-vae-pytorch

A σ-VAE implementation in PyTorch

AsmitaBhat30/skip-vae

AsmitaBhat30/vae-lagging-encoder

PyTorch implementation of "Lagging Inference Networks and Posterior Collapse in Variational Autoencoders" (ICLR 2019)

AsmitaBhat30/vdvae

Repository for the paper "Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images"

AsmitaBhat30/vgan

Code for image generation of Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow

AsmitaBhat30/vqvae

A pytorch implementation of the vector quantized variational autoencoder (https://arxiv.org/abs/1711.00937)

AsmitaBhat30/xfoil-python

Stripped down version of XFOIL as compiled python module