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Implementation Progress

✅ Completed Implementations (30/30)

Core Papers with Full Notebooks

  1. ✅ Paper 1: Complexity Dynamics (01_complexity_dynamics.ipynb)
  2. ✅ Paper 2: Character RNN (02_char_rnn_karpathy.ipynb)
  3. ✅ Paper 3: LSTM Understanding (03_lstm_understanding.ipynb)
  4. ✅ Paper 4: RNN Regularization (04_rnn_regularization.ipynb)
  5. ✅ Paper 5: Neural Network Pruning (05_neural_network_pruning.ipynb)
  6. ✅ Paper 6: Pointer Networks (06_pointer_networks.ipynb)
  7. ✅ Paper 7: AlexNet/CNN (07_alexnet_cnn.ipynb)
  8. ✅ Paper 8: Order Matters - Seq2Seq for Sets (08_seq2seq_for_sets.ipynb)
  9. ✅ Paper 9: GPipe - Pipeline Parallelism (09_gpipe.ipynb)
  10. ✅ Paper 10: ResNet (10_resnet_deep_residual.ipynb)
  11. ✅ Paper 11: Dilated Convolutions (11_dilated_convolutions.ipynb)
  12. ✅ Paper 12: Graph Neural Networks (12_graph_neural_networks.ipynb)
  13. ✅ Paper 13: Attention Is All You Need (13_attention_is_all_you_need.ipynb)
  14. ✅ Paper 14: Bahdanau Attention (14_bahdanau_attention.ipynb)
  15. ✅ Paper 15: Identity Mappings ResNet (15_identity_mappings_resnet.ipynb)
  16. ✅ Paper 16: Relational Reasoning (16_relational_reasoning.ipynb)
  17. ✅ Paper 17: VAE (17_variational_autoencoder.ipynb)
  18. ✅ Paper 18: Relational RNNs (18_relational_rnn.ipynb)
  19. ✅ Paper 19: Coffee Automaton (19_coffee_automaton.ipynb)
  20. ✅ Paper 20: Neural Turing Machines (20_neural_turing_machine.ipynb)
  21. ✅ Paper 21: Deep Speech 2 (CTC) (21_ctc_speech.ipynb)
  22. ✅ Paper 22: Scaling Laws (22_scaling_laws.ipynb)
  23. ✅ Paper 23: MDL Principle (23_mdl_principle.ipynb)
  24. ✅ Paper 24: Machine Super Intelligence (24_machine_super_intelligence.ipynb)
  25. ✅ Paper 25: Kolmogorov Complexity (25_kolmogorov_complexity.ipynb)
  26. ✅ Paper 26: Stanford CS231n - CNN Fundamentals (26_cs231n_cnn_fundamentals.ipynb)
  27. ✅ Paper 27: Multi-Token Prediction (27_multi_token_prediction.ipynb)
  28. ✅ Paper 28: Dense Passage Retrieval (28_dense_passage_retrieval.ipynb)
  29. ✅ Paper 29: RAG (29_rag.ipynb)
  30. ✅ Paper 30: Lost in the Middle (30_lost_in_middle.ipynb)

Statistics

  • Total Papers: 30
  • Implemented: 30 (100%)
  • Remaining: 0 (0%)
  • Coverage: All 30 papers from the Sutskever 30 completed!

Recent Additions (Latest Batch)

Latest implementation:

  1. ✅ Paper 18: Relational RNNs (Dec 2025) - Multi-head self-attention memory, relational reasoning, 3.7% improvement over LSTM baseline

Previous additions:

  1. ✅ Paper 5: Neural Network Pruning (MDL & sparsity)
  2. ✅ Paper 27: Multi-Token Prediction (sample efficiency)