This repository lists all the papers I have read personally1.
Start Day: Oct 28, 2021.
Representation Learning for Treatment Effect Estimation from Observational Data [paper][github][my notes].
Tasty Burgers, Soggy Fries: Probing Aspect Robustness in Aspect-Based Sentiment Analysis [paper][github][my notes].
Causal Inference on Recommender Systems [paper][github][my notes].
Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond [survey paper][my notes].
Scalable Recommendation with Hierarchical Poisson Factorization [paper][my notes].
Contrastive Learning with Hard Negative Samples [paper][my notes] [my related paper]
A Theoretical Analysis of Contrastive Unsupervised Representation Learning [paper][my notes]
Debiased Contrastive Learning [paper][my notes]
Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere [paper][my notes]
Prototypical Contrastive Learning of Unsupervised Representations [paper][my notes]
A Theoretical Analysis of Contrastive Unsupervised Representation Learning [paper][my notes]
A simple framework for contrastive learning of visual representations [paper][my notes]
Measuring in-variances in deep networks [paper][my notes]
Hard negative mixing for contrastive learning [paper][my notes]
Spherical text embedding [paper][my notes]
Conditional negative sampling for contrastive learning of visual representations [paper][my notes]
Approximate nearest neighbor negative contrastive learning for dense text retrieval [paper][my notes]
Auto-Encoding Variational Bayes [paper][my notes]
Self-Damaging Contrastive Learning [paper][video][my notes][my related paper]
What Makes for Good Views for Contrastive Learning? [paper][my notes]
Decoupling Representation and Classifier for Long-Tailed Recognition [paper][my notes]
Class-Balanced Loss Based on Effective Number of Samples [paper][my notes]
Understanding lurkers in online communities: A literature review [paper][my notes]
ECML PKDD 2022 Review (4 papers) + SNAM Review (1 paper)
Learning to reweight examples for robust deep learning [paper][my notes]
News Sharing Networks Expose Information Polluters on Social Media [paper]
[Internship]
Link Prediction Based on Graph Neural Networks [paper]
With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual Representations [paper]
On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines [paper]
Improving Disentangled Text Representation Learning with Information-Theoretic Guidance [paper]
Recommendation as Treatments [paper]
Exploring balanced feature spaces for representation learning [paper]
Shortcut Learning in Deep Neural Networks [paper]
Does Head Label Help for Long-Tailed Multi-Label Text Classification [paper]
Cause-Effect Preservation and Classification using Neurochaos Learning [paper]
Machine Unlearning [paper]