summaries of papers on deep learning.
- [Week-1] 15-Oct-2017 - DL history and basics : DBN, AlexNet, VGGNet, GoogLeNet, ResNet, RNN(speech evolution)
- [Week-2] 22-Oct-2017 - DL methods : models, optimization, deep generative model, rnn/seq-to-seq model
- [Week-3] 29-Oct-2017 - DL methods : Neural Turing Machine,Reinforcement-Transfer-One-Shot Deep Learning
- [Week-4] 06-Nov-2017 - DL applications : nlp, object detection, visual tracking, image caption
- [Week-5] 12-Nov-2017 - DL applications : Machine Translation, Robotics, Art, Object Segmentation
- [Week-6] 19-Nov-2017 - recommender systems
- [Week-7] 26-Nov-2017 - ftm : 01/2011 - 12/2014
- [Week-8] 03-Dec-2017 - ftm : 01/2015 - 12/2015
- [Week-9] 10-Dec-2017 - ftm : 01/2016 - 05/2016
- [Week-10] 17-Dec-2017 - ftm : 06/2016 - 12/2016
- [Week-11] 24-Dec-2017 - ftm : 01/2017 - 07/2017
- [Week-12] 31-Dec-2017 - ftm : 08/2017 - 12/2017
- [Jan-2018]
- [Feb-2018]
- [March-2018]
- [April-2018]
- [May-2018]
- [June-2018]
Articles
10/2018
- The Profiling Machine: Active Generalization over Knowledge
- AI Benchmark: Running Deep Neural Networks on Android Smartphones
- A deep learning pipeline for product recognition on store shelves
- MyCaffe: A Complete C# Re-Write of Caffe with Reinforcement Learning
- Quantum Artificial Life in an IBM Quantum Computer
- Finding Solutions to Generative Adversarial Privacy
- Towards Fast and Energy-Efficient Binarized Neural Network Inference on FPGA
- Scaling Video Analytics Systems to Large Camera Deployments
- From Soft Classifiers to Hard Decisions: How fair can we be?
- AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias
- Comparison of Reinforcement Learning algorithms applied to the Cart Pole problem
- Auto-Keras: Efficient Neural Architecture Search with Network Morphism
- An Overview on Application of Machine Learning Techniques in Optical Networks
- A Tale of Three Probabilistic Families: Discriminative, Descriptive and Generative Models
- Transfer Metric Learning: Algorithms, Applications and Outlooks
- Secure Deep Learning Engineering: A Software Quality Assurance Perspective
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding [code]
- Is multiagent deep reinforcement learning the answer or the question? A brief survey
- CURIOUS: Intrinsically Motivated Multi-Task, Multi-Goal Reinforcement Learning
09/2018
- Hamiltonian Descent Methods
- Deep Learning for Generic Object Detection: A Survey
- Unity: A General Platform for Intelligent Agents
- Five lessons from building a deep neural network recommender for marketplaces
- Focus Group on Artificial Intelligence for Health
- Deep Learning in Information Security
- LiveBot: Generating Live Video Comments Based on Visual and Textual Contexts
- IncSQL: Training Incremental Text-to-SQL Parsers with Non-Deterministic Oracles
- Identifying Real Estate Opportunities using Machine Learning
- Deep Learning Towards Mobile Applications
- HappyDB: A Corpus of 100,000 Crowdsourced Happy Moments
- Urban morphology meets deep learning: Exploring urban forms in one million cities, town and villages across the planet
- Graph Convolutional Networks for Text Classification
- Identifying Generalization Properties in Neural Networks
- Towards Deep and Representation Learning for Talent Search at LinkedIn
- Cellular automata as convolutional neural networks
- Realistic Evaluation of Deep Semi-Supervised Learning Algorithms
- AlphaSeq: Sequence Discovery with Deep Reinforcement Learning
- Learning to Interpret Satellite Images Using Wikipedia
- Visual Analytics for Automated Model Discovery
- GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration
- Stakeholders in Explainable AI
- Adversarial Attacks and Defences: A Survey
- Audio-Visual Speech Recognition With A Hybrid CTC/Attention Architecture
- Deep Learning in Mobile and Wireless Networking: A Survey
08/2018
- Backprop Evolution
- Sparse and Dense Data with CNNs: Depth Completion and Semantic Segmentation
- Large Scale Language Modeling: Converging on 40GB of Text in Four Hours. paper
- RecoGym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising
- Neural Arithmetic Logic Units
- CornerNet: Detecting Objects as Paired Keypoints
- A Survey on Deep Transfer Learning
- YOLO3D: End-to-end real-time 3D Oriented Object Bounding Box Detection from LiDAR Point Cloud
- Dialog-context aware end-to-end speech recognition
- An Efficient Deep Reinforcement Learning Model for Urban Traffic Control
- Predicting Expressive Speaking Style From Text In End-To-End Speech Synthesis
- GeneSys: Enabling Continuous Learning through Neural Network Evolution in Hardware
- Application of End-to-End Deep Learning in Wireless Communications Systems
- A Short Note about Kinetics-600
- Smart City Development with Urban Transfer Learning
- Deep Learning Advances on Different 3D Data Representations: A Survey
- Skill Rating for Generative Models. paper
- Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network. paper
- Hierarchical Attention: What Really Counts in Various NLP Tasks . paper
- Neural Architecture Search: A Survey. paper
- Rapid Adaptation of Neural Machine Translation to New Languages. paper
- A Survey on Sentiment and Emotion Analysis for Computational Literary Studies. paper
- Video-to-Video Synthesis. arxiv [code]
- CoQA: A Conversational Question Answering Challenge. arxiv
- QuAC : Question Answering in Context. arxiv
- Everybody Dance Now. paper
- Contextual Parameter Generation for Universal Neural Machine Translation. paper
- Fusion++: Volumetric Object-Level SLAM. paper
- Mapping Text to Knowledge Graph Entities using Multi-Sense LSTMs
- FPGA Implementation of Convolutional Neural Networks with Fixed-Point Calculations
- Generalisation in humans and deep neural networks
- All You Need is "Love": Evading Hate-speech Detection
07/2018
- Troubling Trends in Machine Learning Scholarship
- Machine Learning in High Energy Physics Community White Paper
- Quasi-Dilemmas for Artificial Moral Agents
- Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences
- Comparing Dynamics: Deep Neural Networks versus Glassy Systems
- Financial Trading as a Game: A Deep Reinforcement Learning Approach
- Natural Language Processing for Information Extraction
- Video Summarisation by Classification with Deep Reinforcement Learning
- Generative models on accelerated neuromorphic hardware
- A Survey of Knowledge Representation and Retrieval for Learning in Service Robotics
- Zipf's law in 50 languages: its structural pattern, linguistic interpretation, and cognitive motivation
- JUMPER: Learning When to Make Classification Decisions in Reading
- Universal Word Segmentation: Implementation and Interpretation
- End-to-End Race Driving with Deep Reinforcement Learning
- Taskonomy: Disentangling Task Transfer Learning
- ClariNet: Parallel Wave Generation in End-to-End Text-to-Speech. arxiv
- Hierarchical Multi Task Learning With CTC. arxiv
- When deep learning meets security. arxiv
- Object Detection with Deep Learning: A Review. arxiv
- Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search. arxiv
- Implementing Neural Turing Machines
- Talk the Walk: Navigating New York City through Grounded Dialogue
- The Lottery Ticket Hypothesis: Finding Small, Trainable Neural Networks
- Learning by Asking Questions
- Deep learning in agriculture: A survey
- Learning Plannable Representations with Causal InfoGAN, ICML / IJCAI / AAMAS 2018 Workshop on(PAL-18).
- Progressive Neural Architecture Search
- Variational Bayesian Reinforcement Learning with Regret Bounds
- Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes
- Learning from Delayed Outcomes with Intermediate Observations
- A Survey of the Usages of Deep Learning in Natural Language Processing
- The GAN Landscape: Losses, Architectures, Regularization, and Normalization
- Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures
- TherML: Thermodynamics of Machine Learning
- Neural Processes
- GAN Q-learning
- LaneNet: Real-Time Lane Detection Networks for Autonomous Driving
- TextWorld: A Learning Environment for Text-based Games, ICML/IJCAI 2018.
- Perceptrons from Memristors
- Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
- Large-Scale Visual Speech Recognition
|| dl-research-groups | dl-frameworks | dl1+dl2 | awesome-dl+roadmap+ml | CB-Insights_AI-100 + AI100_2 | ai-angelList | machine-learning-surveys ||
|| a--rnn | a-deep-vision | a--random-forest | a-computer-vision | a-deep-learning | a-p | d-l-p | drlp | DeepLearningImplementations | drlp2 | dl-papernotes | dl-r | med-appl | very-dl | nn.papers | a-GAN | rl.papers| dnn.med | cuda.programming | caltech.cuda | rtb-papers | deep-learning-nlp-rl-papers | nips2017 | deep_learning_object_detection ||
|| Outline of artificial intelligence | Outline of machine learning | Outline of computer vision | Outline of natural language processing | Outline of robotics | List of datasets for machine learning research| ai applications | UCI.ML.DATASETS | public.datasets | kaggle.datasets | datasets.gh.list ||
|| awesome-nlp | nlp_tasks | DeepNLP-models-Pytorch | oxford.nlp.lectures | stanford.nlp.lectures | nltk.org/book | DL4NLP | cs388.utexas.nlp | nlp-datasets | DL-NLP-Readings | gt-nlp-class ||
ML/DL Publications
- Arxiv Sanity Preserver
- NIPS
- ICML-17
- AAAI
- CVPapers
- arxiv.ml
- arxiv.cvpr
- arxiv.ai
- arxiv.ne
- arxiv.ro
- arxiv.nc
- hinton
- MILA
- FAIR
- deepmind
- brain team
- andrewng
- yann.lecun,nyu
- manning
- hiit.neuro
- grey.colorado.edu.CCNL
- dbsystem
- nvidia.ml.research
- stanford.vision.lab
- BAIR.people + courses
- CSAIL.people + publications
- SAIL.people + courses
- google.machineIntelligence
- google.MachinePerception
- google.MachineTranslation
- google.NaturalLanguageProcessing
- google.AIResidency
- scholar.cvpr
- scholar.ai
- scholar.gt
- scholar.ro
- shoham
- ai.people
- ml.people
- AAAI.fellows
- UTA.ai
- UTA.dml
- wildml
- rl.gh.p
- nn.gh.p
- openai.requests.research
- psy.ox.ac.uk
- cs.ox.ac.uk
- CV.people
- arXivTimes
ML/DL Implementations
- deepmind.gh.code
- openai.gh.code
- facebookresearch.gh.code
- frameworks.dl
- ml.python
- deep.nlp.models.pytorch
- rl
- dl.keras.tf
- pytorch.list
- ml.algorithms
- cnn.benchmarks
- pytorch.tut
- pytorch.ex
- torch.start
- dl.tool
- rl.tf
- DCGAN.tf
- ntm.tf
- neural.style
- torch.rnn
- stanford.dl.ex
- deepq.tf
- gan
- ml.hackers.code.r
- bayesian.code.jn
- nn.dl.code
- nn.java
- ml.go
- numenta.gh.code
- tensorflow.gh.code
- neural.doodle.code
- ml.sf.engineering
- tf.models
- DL4NLP
- neural.style.torch
- opencog
- ml.jn.scikit
- bayesian.PyMC3
- tf.ex
- ALE
- aima.py
- deeplearning4j.code
- tflearn.tf
- resnet
- stanford.tf
- top.dl
- tensorlayer.dl.rl
- dl.keras
- dl.docker
- dl.list
- mila.gh.code
- microsoft.gh.code
- CSAILVision.gh.code
- NVIDIA.gh.code
- OpenNMT.code
- Tencent.code
- baidu.code
- stanfordnlp.code
- sar.ml
- sony.code
- ml
- PrincetonVision.code
- commaai.code
- NervanaSystems.code
- pytorch.code
- torch.code
- automl.code
- chainer.code
- dmlc.code
- BVLC.code
- caffe2.code
- aimacode.code
- opencog.code
- opencv.code
- oxford.deepnlp
- USC.ds.code
- gensim.nlp.ir
- scikit.learn.code
- tesseract.code
- ds.ipython
- ml.book
- ccs.video.cources
- eff.tf
- ml.tut
- swift.ai
- tf.book
- ml.mindmaps
- dl
- h2o.ai
- fast.ai
- tf.tut
- tf.tut
- PipelineAI
- PRML
- mlpack
- mit.nlp
- scikit.learn.contrib
- mit.ml.pdf
- ml.py.book
- onnx.code
- aml.sf
- dmml.sf
- prolog.ai
- deep.rl.1
- deep.rl.pytorch
- dl.tut
- dl.trade
- benchm.ml
- dl.java
- dl.tf
- self-car.ai
- dql
- drl.berkeley
- PAIR-code
- fast.ai
- courses.fast.ai
- cs231n.stanford.edu/
- cs224d.stanford.edu/
- oxford-cs-deepnlp-2017
- UFLDL Tutorial 1
- UFLDL Tutorial 2
- dl.NLP (without Magic)|
- dl.p.dn
- dl.bu
- Theano.tut
- nn.Matlab
- cnn.face
- Torch7.tut
- ml.tut.web
- VGG.cnn
- TensorFlow.tut
- TensorFlow.tut+
- TensorFlow.py.n
- Keras.Lasagne.tut
- TensorFlow.LSTM.RNN
- TensorFlow.World
- dl.py
- Grokking.dl
- dl.Search
- Keras.tut
- Pytorch.tut
- Ray Kurzweil
- Andrew Ng
- Geoff Hinton
- Yann LeCun
- Yoshua bengio
- Jeff Hawkins
- Adam Coates
- Adam Coates
- Adam Coates
- Yann LeCun
- Geoffrey Hinton at GoogleTechTalks
- Jeremy Howard at TEDxBrussels
- Andrew Ng in Stanford (2011)
- Chris Manning in Stanford
- Natalie Hammel and Lorraine Yurshansky
- Steve Jurvetson (and panel) at VLAB in Stanford
- Leo Isikdogan at Motorola Mobility HQ
- CS224u: Natural Language Understanding
- Deep Learning โ a cookbook view
ML/DL conferences in 2018
- aideadlin.es
- /r/MachineLearning/
- conference paper templates
- AI Conferences in 2018
- Calendar of Computer Image Analysis, Computer Vision Conferences
- guide2research
Conference Papers:
highscalability - to dive in all time favorites list
- [Week-1] 19-Nov-2017
- [Week-2] 26-Nov-2017
- [Week-3] 03-Dec-2017
- [Week-4] 10-Dec-2017
- [Week-5] 17-Dec-2017
- [Week-6] 24-Dec-2017
- [Week-7] 31-Dec-2017
- [startupreadings]
- [awesome-scalability]
Blockchain | Ethereum | Bitcoin | LTC | Neo | QTUM | UBIQ |
---|
- [Week-1] 19-Nov-2017 - decentralized systems(Blockchain)
- [Week-2] 26-Nov-2017 - decentralized systems(Blockchain)
- [Week-3] 03-Dec-2017 - bitcoin content
- [Week-4] 17-Dec-2017 - bitcoin code
- [Week-5] 24-Dec-2017 - ethereum content
- [Week-6] 31-Dec-2017 - ethereum programming + ICO
|| blockchain-papers | blockchain in action | awesome-blockchain+influencers+whitepapers+cryptocurrency | ICO+Resources||
Gopala KR / @gopala-kr