2021-05

• code2vec: Learning Distributed Representations of Code [YT]

---

2020-12

• Machine Learning for a Better Developer Experience [Medium]
• DSL Development with Xtext [vimeo]
• Life of a Netflix Partner Engineer — The case of the extra 40 ms [Medium]
• How to spin your scientific research out of a university and into a startup [YC]

2020-11

• Adaptive correction of program statements [ACM]
• Compiling techniques to exploit the pattern of language usage [link]
• Natural information processing [link]

2020-10

• NeuralQA: A Usable Library for Question Answering (Contextual Query Expansion + BERT) on Large Datasets [arXiv]
• T2API: Synthesizing API Code Usage Templates from English Texts with Statistical Translation [ACM]
• NLP2Code: Code Snippet Content Assist via Natural Language Tasks [arXiv]

2020-04

• CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison [arXiv]
• Self-Training for Biomedical Parsing [link]
• How Will You Measure Your Life? [HBR]
• Quantum Computing for Pattern Classification [arXiv]

2020-04

• Mining Change Logs and Release Notes to Understand Software Maintenance and Evolution [ResearchGate]
• Network In Network [arXiv]
• ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases [arXiv]
• Deep learning on unseen data: introducing federated learning [link]
• U-Net: Convolutional Networks for Biomedical Image Segmentation [arXiv] [Medium]
• Consistent Individualized Feature Attribution for Tree Ensembles [arXiv]

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2019-11

• Practical DevOps for the busy Data Scientist [link]
• Human-level control through deep reinforcement learning [nature]
• Deep Reinforcement Learning that Matters (! with interesting Conclusion and Supplementary)[arXiv]
• Self-Supervised Representation Learning [github.io]
• Learning to Predict Without Looking Ahead: World Models Without Forward Prediction [github.io]
• Demonstration of Machine Learning-Based Model-Independent Stabilization of Source Properties in Synchrotron Light Sources [PhysRevLet]
• Accelerated Methods for Deep Reinforcement Learning [arXiv]
• Reproducible Research is more than Publishing Research Artefacts: A Systematic Analysis of Jupyter Notebooks from Research Articles [arXiv]
• Self-training with Noisy Student improves ImageNet classification [arXiv]
• Putting An End to End-to-End: Gradient-Isolated Learning of Representations [arXiv]

2019-10

• A Public Domain Dataset for Human Activity Recognition Using Smartphones [link] [dataset]
• Human Activity Recognition on Smartphones with Awareness of Basic Activities and Postural Transitions [Springer, p. 177] [dataset]
• ETSI GS Quantum Key Distribution (QKD); Application Interface [link]
• Maximal Adaptive-Decision Speedups in Quantum-State Readout [APS]
• Decision Making Photonics Solving Bandit Problems Using Photons [ResearchGate]
• A Reinforcement Learning approach for Quantum State Engineering [arXiv]
• Stable Baselines Tutorial [github.io]
• Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning [github.io]
• Semantic Versioning [link]
• State representation in Reinforcement Learning [stackexchange]
• Troubleshooting Deep Neural Networks [link]

2019-09

• Architectural Principles for a Quantum Internet [IETF]
• A Link Layer Protocol for Quantum Networks [arXiv]
• A Neural Algorithm of Artistic Style [arXiv]

2019-08

• Employee Turnover Prediction with Machine Learning: A Reliable Approach [ResearchGate]
• Machine Learning: The High Interest Credit Card of Technical Debt [ai.google]

2019-07

• Seamless Nudity Censorship: an Image-to-Image Translation Approach based on Adversarial Training [ResearchGate]
• Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks [arXiv] [code]
• XLNet: Generalized Autoregressive Pretraining for Language Understanding [arXiv]
• Towards an Empirical Foundation for Assessing Bayesian Optimization of Hyperparameters [link] [set of benchmark functions provided in the paper were used to benchmark scikit-optimize]
• Unsupervised Data Augmentation for Consistency Training [arXiv]

2019-04

• BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding [arXiv]

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2018-08

• Learning hard quantum distributions with variational autoencoders [nature]
• A fully programmable 100-spin coherent Ising machine with all-to-all connections [science]

2018-07

• Neural-network quantum state tomography [nature]
• Deep learning with coherent nanophotonic circuits [nature]

2018-06

• Quantum Kitchen Sinks: An algorithm for machine learning on near-term quantum computers [arXiv]
• Solving the Quantum Many-Body Problem with Artificial Neural Networks [arXiv]
• QVECTOR: an algorithm for device-tailored quantum error correction [arXiv]

2018-04

• A Quantum Approximate Optimization Algorithm [arXiv]
• A variational eigenvalue solver on a quantum processor [arXiv]
• Quantum principal component analysis [arXiv]
• Quantum Artificial Life in an IBM Quantum Computer [nature]
• A Software Methodology for Compiling Quantum Programs [arXiv]

---

	NLP	RL
2017 fall	[Deep Learning in NLP]	[Deep Reinforcement Learning]
2017 spring	[Deep learning in NLP]	-

2017-10

• Policy Gradient Methods for Reinforcement Learning with Function Approximation [nips]

2017-09

• The CHEMDNER corpus of chemicals and drugs and its annotation principles [PubMed Central]
• Emotion Recognition From Speech With Recurrent Neural Networks [arXiv]

2017-08

• Convolutional neural networks for artistic style transfer [post]
• SQuAD: 100,000+ Questions for Machine Comprehension of Text [arXiv]
• MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text [microsoft]
• DRAGNN: A Transition-based Framework for Dynamically Connected Neural Networks [arXiv]
• Generative Adversarial Nets [arXiv]
• The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology [oncotarget]
• Adversarial Autoencoders [arXiv]
• Latent Intention Dialogue Models [link]

2017-07

• {+} Annotated Chemical Patent Corpus: A Gold Standard for Text Mining [link]
• Event-based text mining for biology and functional genomics [link]
• OSCAR4: a flexible architecture for chemical text-mining [link]
• Word Representations via Gaussian Embedding [arXiv]
• Gaussian Mixture Embeddings for Multiple Word Prototypes [arXiv]
• Multimodal Word Distributions [arXiv]

2017-06

• Canonical Correlation Analysis For Classifying Baby Crying Sound Events [link]
• Seq2seq-Attention Question Answering Model [link]

2017-05

• Approximating the Kullback Leibler Divergence Between Gaussian Mixture Models [ResearchGate]
• Attention Is All You Need [arXiv]

2017-04

• What is a variational autoencoder? [post]
• Show, Attend and Tell: Neural Image Caption Generation with Visual Attention [arXiv]
• Attention and Memory in Deep Learning and NLP [link]
• Turing Computation with Recurrent Artificial Neural Networks [arXiv]
• How to Code and Understand DeepMind's Neural Stack Machine [post]
• SimpleDS: A Simple Deep Reinforcement Learning Dialogue System [arXiv]
• On the universal structure of human lexical semantics [PNAS]
• Understanding LSTM Networks [post]
• Recurrent Neural Network Grammars [arXiv]

2017-03

• Explaining and illustrating orthogonal initialization for recurrent neural networks [post]
• Massive Exploration of Neural Machine Translation Architectures [arXiv]
• The Greening of Blockchains [post]
• Reinforcement Learning for Trading [link]
• Image Style Transfer, Neural Doodles & Texture Synthesis [YT] [slides]
• Distributed Representations of Sentences and Documents [link]
• Stock Trading with Recurrent Reinforcement Learning (RRL) [link] [working code]

2017-02

• Reinforcement Learning for Market-Making [YT]
• New Territory of Machine Translation [YT]
• A Multiagent Approach to Q-Learning for Daily Stock Trading [link]
• A genetic algorithm enabled ensemble for unsupervised medical term extraction from clinical letters [link]

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	NLP	RL
2016 fall	[Natural language processing]	[Reinforcement learning]