Date
|
Name
|
Paper number
|
Title
|
Link to the paper
|
Link to the summary
|
Link to the video
|
Sep 15 (example) |
Ri Wang |
|
Sequence to sequence learning with neural networks. |
Paper |
Summary |
Presentation
|
Week of Nov 11 |
|
1 |
|
|
|
[Presentation ]
|
Week of Nov 11 |
Abhinav Chanana |
2 |
AUGMIX: A Simple Data Procession method to Improve Robustness And Uncertainity |
Paper |
Summary |
[Presentation ]
|
Week of Nov 11 |
Maziar Dadbin |
3 |
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations |
paper |
Summary |
|
Week of Nov 11 |
John Landon Edwards |
4 |
From Variational to Deterministic Autoencoders |
Paper |
Summary |
Presentation
|
Week of Nov 11 |
Wenyu Shen |
5 |
Pre-training of Deep Bidirectional Transformers for Language Understanding |
Paper |
Summary |
Presentation video
|
Week of Nov 11 |
Syed Saad Naseem |
6 |
Learning The Difference That Makes A Difference With Counterfactually-Augmented Data |
Paper |
Summary |
Presentation video
|
Week of Nov 9 |
Donya Hamzeian |
7 |
The Curious Case of Neural Text Degeneration |
Paper |
Summary |
|
Week of Nov 9 |
Parsa Torabian |
8 |
Orthogonal Gradient Descent for Continual Learning |
Paper |
Summary |
Learn
|
Week of Nov 9 |
Arash Moayyedi |
9 |
When Does Self-supervision Improve Few-shot Learning? |
Paper |
Summary |
Learn
|
Week of Nov 9 |
Parsa Ashrafi Fashi |
10 |
Learning to Generalize: Meta-Learning for Domain Generalization |
Paper |
Summary |
Presentation Video
|
Week of Nov 9 |
Jaskirat Singh Bhatia |
11 |
A FAIRCOMPARISON OFGRAPHNEURALNETWORKSFORGRAPHCLASSIFICATION |
Paper |
Summary |
Presentation
|
Week of Nov 9 |
Gaurav Sikri |
12 |
BREAKING CERTIFIED DEFENSES: SEMANTIC ADVERSARIAL EXAMPLES WITH SPOOFED ROBUSTNESS CERTIFICATES |
Paper |
Summary |
[Presentation ]
|
Week of Nov 16 |
Abhinav Jain |
13 |
The Logical Expressiveness of Graph Neural Networks |
Paper |
Summary |
Presentation
|
Week of Nov 16 |
Gautam Bathla |
14 |
One-Shot Object Detection with Co-Attention and Co-Excitation |
Paper |
Summary |
Presentation
|
Week of Nov 16 |
Shikhar Sakhuja |
15 |
SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems |
Paper |
Summary |
[Presentation ]
|
Week of Nov 16 |
Cameron Meaney |
16 |
Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations |
Paper |
Summary |
Learn
|
Week of Nov 16 |
Sobhan Hemati |
17 |
Adversarial Fisher Vectors for Unsupervised Representation Learning |
Paper |
Summary |
video
|
Week of Nov 16 |
Milad Sikaroudi |
18 |
Domain Genralization via Model Agnostic Learning of Semantic Features |
Paper |
Summary |
video also available on Learn
|
Week of Nov 23 |
Bowen You |
19 |
DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION |
Paper |
Summary |
Learn
|
Week of Nov 23 |
Nouha Chatti |
20 |
This Looks Like That: Deep Learning for Interpretable Image Recognition |
Paper |
Summary |
|
Week of Nov 23 |
Mohan Wu |
21 |
Pretrained Generalized Autoregressive Model with Adaptive Probabilistic Label Cluster for Extreme Multi-label Text Classification |
Paper |
Summary |
video
|
Week of Nov 23 |
Xinyi Yan |
22 |
Dense Passage Retrieval for Open-Domain Question Answering |
Paper |
Summary |
Learn
|
Week of Nov 23 |
Meixi Chen |
23 |
Functional Regularisation for Continual Learning with Gaussian Processes |
Paper |
Summary |
Learn
|
Week of Nov 23 |
Ahmed Salamah |
24 |
AdaCompress: Adaptive Compression for Online Computer Vision Services |
Paper |
Summary |
video or Learn
|
Week of Nov 23 |
Mohammad Mahmoud |
32 |
Mathematical Reasoning in Latent Space |
[1] |
|
|
Week of Nov 30 |
Danial Maleki |
25 |
RoBERTa: A Robustly Optimized BERT Pretraining Approach |
Paper |
Summary |
Presentation Video
|
Week of Nov 30 |
Gursimran Singh |
26 |
BERTScore: Evaluating Text Generation with BERT |
Paper |
Summary |
Learn
|
Week of Nov 30 |
Govind Sharma |
27 |
Time-series Generative Adversarial Networks |
Paper |
Summary |
video or Learn
|
Week of Nov 30 |
Maral Rasoolijaberi |
28 |
A critical analysis of self-supervision, or what we can learn from a single image |
Paper |
Summary |
YouTube
|
Week of Nov 30 |
Sina Farsangi |
29 |
Self-Supervised Learning of Pretext-Invariant Representations |
Paper |
Summary |
YouTube or Learn
|
Week of Nov 30 |
Pierre McWhannel |
30 |
Pre-training Tasks for Embedding-based Large-scale Retrieval |
Paper |
Summary |
Learn
|
Week of Nov 30 |
Wenjuan Qi |
31 |
Network Deconvolution |
Paper |
placeholder |
|