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Showing below up to 50 results in range #321 to #370.
- ShakeDrop Regularization (00:34, 17 December 2018)
- CapsuleNets (00:36, 17 December 2018)
- Fix your classifier: the marginal value of training the last weight layer (00:39, 17 December 2018)
- a neural representation of sketch drawings (00:40, 17 December 2018)
- Fairness Without Demographics in Repeated Loss Minimization (00:42, 17 December 2018)
- DON'T DECAY THE LEARNING RATE , INCREASE THE BATCH SIZE (13:28, 17 December 2018)
- learn what not to learn (13:38, 17 December 2018)
- stat441F18 (11:33, 5 September 2020)
- f11Stat841presentation (12:49, 6 October 2020)
- f11Stat841proposal (14:56, 11 October 2020)
- stat946F20/GradientLess Descent (16:17, 31 October 2020)
- ALBERT (11:44, 2 November 2020)
- Meta-Learning-For-Domain Generalization (15:47, 9 November 2020)
- Task Understanding from Confushing Multitask Data (19:25, 15 November 2020)
- Influenza Forecasting Framework based on Gaussian processes Summary (00:02, 16 November 2020)
- Pre-Training-Tasks-For-Embedding-Based-Large-Scale-Retrieval (19:52, 17 November 2020)
- stat841f11 (12:30, 18 November 2020)
- f17Stat946PaperSignUp (19:28, 19 November 2020)
- ModelFramework.jpg (13:14, 24 November 2020)
- Improving neural networks by preventing co-adaption of feature detectors 2020 Fall (22:41, 26 November 2020)
- time-series-using-GAN (21:02, 1 December 2020)
- From Variational to Deterministic Autoencoders (19:11, 2 December 2020)
- Streaming Bayesian Inference for Crowdsourced Classification (23:20, 4 December 2020)
- IPBoost (00:18, 5 December 2020)
- Semantic Relation Classification——via Convolution Neural Network (21:25, 5 December 2020)
- Breaking Certified Defenses: Semantic Adversarial Examples With Spoofed Robustness Certificates (06:58, 6 December 2020)
- Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations (15:51, 6 December 2020)
- SuperGLUE (16:58, 6 December 2020)
- THE LOGICAL EXPRESSIVENESS OF GRAPH NEURAL NETWORKS (17:02, 6 December 2020)
- Adversarial Fisher Vectors for Unsupervised Representation Learning (17:50, 6 December 2020)
- Augmix: New Data Augmentation method to increase the robustness of the algorithm (18:44, 6 December 2020)
- Learning The Difference That Makes A Difference With Counterfactually-Augmented Data (19:42, 6 December 2020)
- One-Shot Object Detection with Co-Attention and Co-Excitation (21:53, 6 December 2020)
- what game are we playing (23:55, 6 December 2020)
- Going Deeper with Convolutions (00:29, 7 December 2020)
- Meta-Learning For Domain Generalization (00:41, 7 December 2020)
- a fair comparison of graph neural networks for graph classification (00:54, 7 December 2020)
- Influenza Forecasting Framework based on Gaussian Processes (14:13, 7 December 2020)
- Neural ODEs (15:01, 7 December 2020)
- Adversarial Attacks on Copyright Detection Systems (15:03, 7 December 2020)
- Task Understanding from Confusing Multi-task Data (15:35, 7 December 2020)
- Graph Structure of Neural Networks (17:06, 7 December 2020)
- Extreme Multi-label Text Classification (22:04, 7 December 2020)
- Mask RCNN (22:37, 7 December 2020)
- Dense Passage Retrieval for Open-Domain Question Answering (22:57, 7 December 2020)
- Functional regularisation for continual learning with gaussian processes (23:25, 7 December 2020)
- orthogonal gradient descent for continual learning (23:30, 7 December 2020)
- Superhuman AI for Multiplayer Poker (00:06, 8 December 2020)
- Adacompress: Adaptive compression for online computer vision services (00:07, 8 December 2020)
- Summary for survey of neural networked-based cancer prediction models from microarray data (00:08, 8 December 2020)
