| 1. | [BERT] Pretranied Deep Bidirectional Transformers for Language Understanding (algorithm) | TDLS | 1,000 | |
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| 2. | [Transformer] Attention Is All You Need | AISC Foundational | 687 | |
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| 3. | [Variational Autoencoder] Auto-Encoding Variational Bayes | AISC Foundational | 458 | |
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| 4. | [Original ResNet paper] Deep Residual Learning for Image Recognition | AISC | 334 | |
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| 5. | Classification of sentiment reviews using n-gram machine learning approach | 271 | Review |
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| 6. | TGN: Temporal Graph Networks for Deep Learning on Dynamic Graphs [Paper Explained by the Author] | 245 | |
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| 7. | Code Review: Transformer - Attention Is All You Need | AISC | 244 | Review |
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| 8. | Principles of Riemannian Geometry in Neural Networks | TDLS | 229 | |
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| 9. | (Original Paper) Latent Dirichlet Allocation (algorithm) | AISC Foundational | 221 | |
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| 10. | Combining Satellite Imagery and machine learning to predict poverty | 213 | |
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| 11. | [ELMo] Deep Contextualized Word Representations | AISC | 213 | |
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| 12. | Introduction to the Conditional GAN - A General Framework for Pixel2Pixel Translation | 198 | |
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| 13. | [GAT] Graph Attention Networks | AISC Foundational | 181 | |
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| 14. | [StyleGAN] A Style-Based Generator Architecture for GANs, part 1 (algorithm review) | TDLS | 180 | Review |
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| 15. | Deep InfoMax: Learning deep representations by mutual information estimation and maximization | AISC | 146 | Guide |
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| 16. | AlphaStar explained: Grandmaster level in StarCraft II with multi-agent RL | 145 | Let's Play | StarCraft II
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| 17. | A Literature Review on Graph Neural Networks | 139 | Review |
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| 18. | Neural Ordinary Differential Equations - part 1 (algorithm review) | AISC | 138 | Review |
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| 19. | Mathematics of Deep Learning Overview | AISC Lunch & Learn | 130 | |
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| 20. | Learning Mesh-Based Simulation with Graph Networks - Tobias Pfaff (DeepMind) | 127 | |
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| 21. | Convolutional Neural Networks for processing EEG signals | 126 | |
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| 22. | Battery Modelling using Data-Driven Machine Learning | AISC | 122 | |
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| 23. | Can deep learning AI help with detecting COVID-19/coronavirus? | 122 | |
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| 24. | Lagrangian Neural Networks | AISC | 117 | |
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| 25. | Leaf Doctor: Plant Disease Detection Using Image Classification | Deep Learning Workshop Capstone | 116 | |
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| 26. | Tobias Pfaff (DeepMind): Learning to Simulate Complex Physics with Graph Networks | 112 | |
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| 27. | Steve Brunton: Machine Learning for Fluid Dynamics | 111 | |
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| 28. | All-optical machine learning using diffractive deep neural networks | TDLS | 109 | |
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| 29. | Connectionist Temporal Classification, Labelling Unsegmented Sequence Data with RNN | TDLS | 105 | |
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| 30. | Deep Neural Networks for YouTube Recommendation | AISC Foundational | 102 | |
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| 31. | [AlphaGo Zero] Mastering the game of Go without human knowledge | TDLS | 98 | Let's Play |
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| 32. | Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyond | TDLS | 97 | |
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| 33. | PGGAN | Progressive Growing of GANs for Improved Quality, Stability, and Variation (part 1) | AISC | 95 | |
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| 34. | Graph Neural Networks, Session 6: DeepWalk and Node2Vec | 88 | |
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| 35. | [DDQN] Deep Reinforcement Learning with Double Q-learning | TDLS Foundational | 88 | |
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| 36. | [GQN] Neural Scene Representation and Rendering | AISC | 86 | |
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| 37. | Revolutionary Deep Learning Method to Denoise EEG Brainwaves | 84 | |
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| 38. | Explainable AI for Time Series - Literature Review | AISC | 84 | Review |
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| 39. | Introduction to NVIDIA NeMo - A Toolkit for Conversational AI | AISC | 82 | |
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| 40. | Transformer XL | AISC Trending Papers | 80 | |
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| 41. | Explainable AI with Layer-wise Relevance Propagation (LRP) | 79 | |
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| 42. | [OpenAI GPT2] Language Models are Unsupervised Multitask Learners | TDLS Trending Paper | 78 | |
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| 43. | Neural Image Caption Generation with Visual Attention (algorithm) | AISC | 76 | |
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| 44. | AlphaFold 2, Is Protein Folding Solved? | AISC | 75 | Let's Play |
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| 45. | Plug and Play Language Models: A Simple Approach to Controlled Text Generation | AISC | 74 | |
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| 46. | Similarity of neural network representations revisited | 73 | |
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| 47. | Reinforcement Learning in Economics and Finance | AISC | 73 | |
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| 48. | Junction Tree Variational Autoencoder for Molecular Graph Generation | TDLS | 72 | |
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| 49. | Graph Normalizing Flows | 72 | |
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| 50. | [Original attention] Neural Machine Translation by Jointly Learning to Align and Translate | AISC | 70 | |
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| 51. | Deep Q-Learning paper explained: Human-level control through deep reinforcement learning (algorithm) | 69 | |
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| 52. | Top-K Off-Policy Correction for a REINFORCE Recommender System | AISC | 62 | |
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| 53. | Topological Deep Learning | 61 | Vlog |
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| 54. | [SAGAN] Self-Attention Generative Adversarial Networks | TDLS | 60 | |
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| 55. | [StackGAN++] Realistic Image Synthesis with Stacked Generative Adversarial Networks | AISC | 56 | |
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| 56. | Logeo: Automatically Transform 2D Designs to 3D | 55 | Vlog |
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| 57. | Ernie 2.0: A Continual Pre-Training Framework for Language Understanding | AISC | 53 | |
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| 58. | An overview of task-oriented dialog systems | AISC | 53 | Vlog |
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| 59. | TMLS2017: Transitioning to Data Science, Panel Discussion | 52 | Discussion |
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| 60. | Machine Learning in Environmental Science and Prediction: An Overview | AISC | 51 | |
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| 61. | Supercharging AI with high performance distributed computing | 51 | |
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| 62. | Single Headed Attention RNN: Stop Thinking With Your Head | AISC | 50 | |
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| 63. | A Literature Review on Machine Learning in Materials Science | AISC | 50 | Review |
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| 64. | [hgraph2graph] Hierarchical Generation of Molecular Graphs using Structural Motifs | AISC Spotlight | 49 | |
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| 65. | [Original Style Transfer] A Neural Algorithm of Artistic Style | TDLS Foundational | 49 | |
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| 66. | Overview of Machine Learning for Knowledge Graphs | AISC | 48 | |
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| 67. | Applications of Blockchain to IoT Security | AISC | 48 | |
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| 68. | Principal Neighbourhood Aggregation for Graph Nets | AISC | 47 | |
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| 69. | Learning the Graphical Structure of Electronic Health Records with Graph Convolutional Transformer | 47 | |
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| 70. | Automated Vulnerability Detection in Source Code Using Deep Learning (algorithm) | AISC | 46 | |
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| 71. | Why do large batch sized trainings perform poorly in SGD? - Generalization Gap Explained | AISC | 45 | |
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| 72. | Deep Learning for Symbolic Mathematics | AISC | 45 | |
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| 73. | The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words & Sentences From Natural Supervision | 45 | |
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| 74. | Lookahead Optimizer: k steps forward, 1 step back | 44 | |
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| 75. | Paper Explained : PEGASUS, a SOTA abstractive summarization model by Google | AISC | 44 | |
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| 76. | A Framework for Developing Deep Learning Classification Models | 44 | |
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| 77. | BERT & NLP Explained | 44 | Let's Play |
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| 78. | [Gated-SCNN] Gated Shape CNNs for Semantic Segmentation | 44 | |
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| 79. | Genomics with Deep Learning: A Concise Overview | AISC | 44 | |
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| 80. | Interpretable Neural Networks for Panel Data Analysis in Economics | AISC | 43 | |
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| 81. | Deep learning enables rapid identification of potent DDR1 kinase inhibitors | AISC | 43 | |
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| 82. | Da Xu (Walmart Labs): Inductive Representation Learning on Temporal Graphs | AISC | 42 | |
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| 83. | XLNet: Generalized Autoregressive Pretraining for Language Understanding | AISC | 41 | |
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| 84. | TF-Encrypted: Private machine learning in tensorflow with secure computing | AISC Lunch & Learn | 39 | |
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| 85. | Neural Ordinary Differential Equations - part 2 (results & discussion) | AISC | 39 | Discussion |
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| 86. | New Directions in Computer Vision | 38 | |
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| 87. | BERTology Meets Biology: Interpreting Attention in Protein Language Models | AISC | 38 | Vlog |
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| 88. | Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods | AISC | 38 | |
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| 89. | State of Natural Language Processing in 2019 | AISC | 38 | |
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| 90. | Understanding the Origins of Bias in Word Embeddings | 37 | |
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| 91. | [RoBERT & ToBERT] Hierarchical Transformers for Long Document Classification | AISC | 36 | |
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| 92. | GrowNet: Gradient Boosting Neural Networks | AISC | 36 | |
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| 93. | Unsupervised Data Augmentation | AISC | 36 | |
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| 94. | Beyond Accuracy: Behavioral Testing of NLP Models with CheckList | AISC | 36 | Let's Play |
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| 95. | Tensor Field Networks | AISC | 34 | |
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| 96. | Explainable AI to Automate Loan Underwriting Decisions | AISC | 34 | |
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| 97. | Visualizing Data using t-SNE (algorithm) | AISC Foundational | 34 | |
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| 98. | Overview of Unsupervised & Semi-supervised learning | AISC | 34 | |
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| 99. | Survival regression with AFT model in XGBoost | AISC | 34 | |
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| 100. | 'Less Than One'-Shot Learning (author speaking) | 34 | |
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