wangxinyilinda Goto Github PK
Name: Xinyi Wang
Type: User
Company: UCSB
Bio: I'm a forth-year Ph.D. student at UCSB CS department.
Twitter: XinyiWang98
Location: Waterloo, Canada
Xinyi Wang's Projects
adaptive-count-ception
This the repository for HKUST COMP4901J final project. We add some residual adapters to the coun-ception network so that it can quickly adapt to new domain.
adversarial-attacks-pytorch
PyTorch implementation of adversarial attacks.
causal-balancing-for-domain-generalization
This is the official reporsitory for paper Causal Balancing for Domain Generalization
cmle
This is the repository for the paper: Counterfactual Maximum Likelihood Estimation for Training Deep Networks.
concept-based-demonstration-selection
Offical code of the paper Large Language Models Are Implicitly Topic Models: Explaining and Finding Good Demonstrations for In-Context Learning.
deep-q-learning-bitcoin-trading-agent
The first half of my capstone project implementing Bitcoin trading agent using deep Q learning.
lm_random_walk
Official code for paper Understanding the Reasoning Ability of Language Models From the Perspective of Reasoning Paths Aggregation
lxmert
PyTorch code for EMNLP 2019 paper "LXMERT: Learning Cross-Modality Encoder Representations from Transformers".
neural-topic-model-with-attention-for-supervised-learning
This the repository for the AISTATS 2020 paper Neural Topic Model with Attention for Supervised Learning.
planning_tokens
Official code for Guiding Language Model Math Reasoning with Planning Tokens
policy-gradient-trading-algorithm-by-maximizing-sharpe-ratio
The second half of my capstone project, proposing a deep policy gradient algorithm for auto-trading by directly maximizing the Sharpe ratio.
pytorch-vq-vae
PyTorch implementation of VQ-VAE by Aäron van den Oord et al.
q_learning_for_trading_web_app
This is the repo of my COMP4021 final project.
self-critical.pytorch
Unofficial pytorch implementation for Self-critical Sequence Training for Image Captioning. and others.
time-sensitive-qa
Code and Data for NeurIPS2021 Paper "A Dataset for Answering Time-Sensitive Questions"
transformers
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
vae-cvae-mnist
Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch
vlp
Vision-Language Pre-training for Image Captioning and Question Answering
vq-vae-2-pytorch
Implementation of Generating Diverse High-Fidelity Images with VQ-VAE-2 in PyTorch
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