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273 lines
13 KiB
Markdown
273 lines
13 KiB
Markdown
# Resources for Quantum Computing Machine Learning
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## Introductory Concepts
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#### Atom Structure
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* [A nice animation video about the basic atom structure](https://www.youtube.com/watch?v=g_IaVepNDT4).
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#### Photon Wave
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* [A nice animation video about the basic atom structure](https://www.youtube.com/watch?v=fwXQjRBLwsQ)
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* [A nice animation video about the basic photon](https://www.youtube.com/watch?v=KKr91v7yLcM).
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#### Electron Fluctuation or spin
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* [A nice animation video about the basic Electron Spin](https://www.youtube.com/watch?v=J3xLuZNKhlY).
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* [A nice animation video about the basic Electron Spin](https://www.youtube.com/watch?v=3k5IWlVdMbo).
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* [A nice animation video about the basic Electron Spin](https://www.youtube.com/watch?v=jvvkomcmyuo).
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#### States
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* [A nice animation video about the Quantum States](https://www.youtube.com/watch?v=sICXOwOwS4E).
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#### SuperPosition
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* [A nice animation video about the Quantum Superposition.](https://www.youtube.com/watch?v=hkmoZ8e5Qn0)
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#### SuperPosition specific for machine learning (Quantum Walks)
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* [A nice video about the Quantum Walks.](https://www.youtube.com/watch?v=86QsYPxoBow)
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#### Qubit
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* [A nice video about the Quantum Bits.](https://www.youtube.com/watch?v=zNzzGgr2mhk)
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* [A nice video about the Quantum Bits.](https://www.youtube.com/watch?v=F8U1d2Hqark&t=179s)
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#### Basic Gates in Quantum Computing
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* [A nice video about the Quantum Gates.](https://www.youtube.com/watch?v=2Qsh_w2kq9Y)
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#### Quantum Diode
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* [A nice video about the Quantum Diode.](https://www.youtube.com/watch?v=doyK1olswX4)
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#### Quantum Transistors
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* [Discussion about the Quantum Transistor.](https://www.quora.com/What-is-the-equivalent-of-the-transistor-in-a-quantum-computer)
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* [A nice video about quantum transistor.](https://www.youtube.com/watch?v=ZTxR2n2mvjc)
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#### Quantum Processor
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* [A nice video about quantum processor.](https://www.youtube.com/watch?v=CMdHDHEuOUE)
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#### Quantum Registery QRAM
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* [A paper explaining QRAM.](https://arxiv.org/pdf/0807.4994.pdf)
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#### Complex Numbers
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* [Series of explanation.](https://www.youtube.com/watch?v=T647CGsuOVU)
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#### Tensors
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* [Series of explanation.](https://www.youtube.com/watch?v=f5liqUk0ZTw)
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* [Quantum tensors basics.](https://www.youtube.com/watch?v=xzG6c96PsLs)
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#### Tensors Network
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* [Tensors Network Some ideas specifically for quantum algorithms.](https://www.youtube.com/watch?v=bD-CWgbsCeI&list=PLgKuh-lKre10UQnP7gBCFoKgq5KWIA7el)
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#### Quantum K-Means
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* [Applying Quantum Kmeans on Images](https://pdfs.semanticscholar.org/6d77/54d33958b4a41d57ec99558eb28ae88f9884.pdf).
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#### Quantum Fuzzy C-Means
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* [QFuzzy theory](https://pdfs.semanticscholar.org/6d77/54d33958b4a41d57ec99558eb28ae88f9884.pdf).
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#### Quantum Support Vector Machine
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* [Nice paper explanation.](https://arxiv.org/pdf/1307.0471.pdf)
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* [Nice Application of QSVM.](http://www.scirp.org/journal/PaperInformation.aspx?paperID=72542)
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#### Quantum Genetic Algorithm
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* [Very Beautiful Article.](https://www.hindawi.com/journals/mpe/2013/730749/)
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* [Very Beautiful Article.](https://arxiv.org/pdf/1202.2026.pdf)
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#### Quantum Hidden Morkov Models
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* [Very Beautiful Article.](https://arxiv.org/pdf/1503.08760.pdf)
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#### Quantum state classification with Bayesian methods
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* [Very Beautiful Article.](https://arxiv.org/pdf/1204.1550.pdf)
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* [Very Beautiful Article.](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4726808/)
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#### Quantum Ant Colony Optimization
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* [Very Beautiful Article.](http://ac.els-cdn.com/S2212667812001359/1-s2.0-S2212667812001359-main.pdf?_tid=42e0cd66-2f4a-11e7-920f-00000aacb361&acdnat=1493738345_8f536599e404c7588811ddd49c484688)
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#### Quantum Cellular Automata
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* [Very Beautiful Article.](https://arxiv.org/pdf/0808.0679.pdf)
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* [Very Beautiful Article.](http://ieee-hpec.org/2013/index_htm_files/7-Improved-Eigensolver-Baldwin-2867489.pdf)
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#### Quantum perceptrons
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* [Very Beautiful Article.](https://arxiv.org/pdf/quant-ph/0201144.pdf)
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* [Very Beautiful Article.](http://axon.cs.byu.edu/papers/ricks.nips03.pdf/)
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------
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## TED Talks related to Quantum Computing
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1. A beginner's guide to quantum computing:
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https://www.ted.com/talks/shohini_ghose_quantum_computing_explained_in_10_minutes#t-322340
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2. What can Schrödinger's cat teach us about quantum mechanics?
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https://www.ted.com/talks/josh_samani_what_can_schrodinger_s_cat_teach_us_about_quantum_mechanics#t-323151
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3. Schrödinger's cat: A thought experiment in quantum mechanics:
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https://www.ted.com/talks/chad_orzel_schrodinger_s_cat_a_thought_experiment_in_quantum_mechanics#t-263061
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4. What is the Heisenberg Uncertainty Principle?
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https://www.ted.com/talks/chad_orzel_what_is_the_heisenberg_uncertainty_principle#t-259830
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5. How quantum physics can make encryption stronger:
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https://www.ted.com/talks/vikram_sharma_how_quantum_physics_can_make_encryption_stronger#t-701357
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6. How quantum biology might explain life's biggest questions:
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https://www.ted.com/talks/jim_al_khalili_how_quantum_biology_might_explain_life_s_biggest_questions#t-394875
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7. Making sense of a visible quantum object:
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https://www.ted.com/talks/aaron_o_connell_making_sense_of_a_visible_quantum_object#t-9460
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8. The future of supercomputers? A quantum chip colder than outer space:
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https://www.ted.com/talks/jerry_chow_the_future_of_supercomputers_a_quantum_chip_colder_than_outer_space#t-1807
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9. What's the smallest thing in the universe?
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https://www.ted.com/talks/jonathan_butterworth_what_s_the_smallest_thing_in_the_universe#t-305865
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----
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## Reviews
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* [Quantum Machine Learning: What Quantum Computing Means to Data Mining](https://www.researchgate.net/publication/264825604_Quantum_Machine_Learning_What_Quantum_Computing_Means_to_Data_Mining) (2014)
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* [Quantum Machine Learning](https://arxiv.org/abs/1611.09347v2) (2016)
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* [A Survey of Quantum Learning Theory](https://arxiv.org/abs/1701.06806) (2017)
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* [Quantum Machine Learning: a classical perspective](https://arxiv.org/abs/1707.08561) (2017)
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* [Opportunities and challenges for quantum-assisted machine learning in near-term quantum computers](https://arxiv.org/abs/1708.09757) (2017)
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* [Quantum machine learning for data scientists](https://arxiv.org/abs/1804.10068) (2018)
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* [Supervised Learning with Quantum Computers](https://www.springer.com/gp/book/9783319964232) (2018)
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----
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## Discrete-variables quantum computing
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### Theory
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* [Quantum Statistical Inference](https://arxiv.org/abs/1812.04877) (2018)
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* [Quantum hardness of learning shallow classical circuits](https://arxiv.org/abs/1903.02840) (2019)
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### Variational circuits
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* [Quantum Boltzmann Machine](https://arxiv.org/abs/1601.02036) (2016)
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* [Quantum Perceptron Model](https://arxiv.org/abs/1602.04799) (2016)
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* [Quantum autoencoders via quantum adders with genetic algorithms](https://arxiv.org/abs/1709.07409) (2017)
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* [A Quantum Hopfield Neural Network](https://arxiv.org/abs/1710.03599) (2017)
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* [Automated optimization of large quantum circuits with continuous parameters](https://arxiv.org/abs/1710.07345) (2017)
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* [Quantum Neuron: an elementary building block for machine learning on quantum computers](https://arxiv.org/abs/1711.11240) (2017)
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* [A quantum algorithm to train neural networks using low-depth circuits](https://arxiv.org/abs/1712.05304) (2017)
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* [A generative modeling approach for benchmarking and training shallow quantum circuits](https://arxiv.org/abs/1801.07686) (2018)
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* [Universal quantum perceptron as efficient unitary approximators](https://arxiv.org/abs/1801.00934) (2018)
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* [Quantum Variational Autoencoder](https://arxiv.org/abs/1802.05779) (2018)
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* [Classification with Quantum Neural Networks on Near Term Processors](https://arxiv.org/abs/1802.06002) (2018)
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* [Barren plateaus in quantum neural network training landscapes](https://arxiv.org/abs/1803.11173) (2018)
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* [Quantum generative adversarial learning](https://arxiv.org/abs/1804.09139) (2018)
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* [Quantum generative adversarial networks](https://arxiv.org/abs/1804.08641) (2018)
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* [Circuit-centric quantum classifiers](https://arxiv.org/abs/1804.00633) (2018)
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* [Universal discriminative quantum neural networks](https://arxiv.org/abs/1805.08654) (2018)
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* [A Universal Training Algorithm for Quantum Deep Learning](https://arxiv.org/abs/1806.09729) (2018)
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* [Bayesian Deep Learning on a Quantum Computer](https://arxiv.org/abs/1806.11463) (2018)
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* [Quantum generative adversarial learning in a superconducting quantum circuit](https://arxiv.org/abs/1808.02893) (2018)
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* [The Expressive Power of Parameterized Quantum Circuits](https://arxiv.org/abs/1810.11922) (2018)
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* [Quantum Convolutional Neural Networks](https://arxiv.org/abs/1810.03787) (2018)
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* [An Artificial Neuron Implemented on an Actual Quantum Processor](https://arxiv.org/pdf/1811.02266.pdf) (2018)
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* [Graph Cut Segmentation Methods Revisited with a Quantum Algorithm](https://arxiv.org/abs/1812.03050) (2018)
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* [Efficient Learning for Deep Quantum Neural Networks](https://arxiv.org/abs/1902.10445) (2019)
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* [Parameterized quantum circuits as machine learning models](https://arxiv.org/abs/1906.07682) (2019)
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* [Machine Learning Phase Transitions with a Quantum Processor](https://arxiv.org/abs/1906.10155) (2019)
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### Tensor Networks
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* [Towards Quantum Machine Learning with Tensor Networks](https://arxiv.org/abs/1803.11537) (2018)
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* [Hierarchical quantum classifiers](https://arxiv.org/abs/1804.03680v1) (2018)
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### Reinforcement learning
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* [Quantum reinforcement learning](https://arxiv.org/abs/0810.3828) (2008)
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* [Reinforcement Learning Using Quantum Boltzmann Machines](https://arxiv.org/abs/1612.05695) (2016)
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* [Generalized Quantum Reinforcement Learning with Quantum Technologies](https://arxiv.org/abs/1709.07848) (2017)
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### Optimization
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* [Quantum gradient descent and Newton’s method for constrained polynomial optimization](https://arxiv.org/abs/1612.01789) (2016)
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* [Quantum algorithms and lower bounds for convex optimization](https://arxiv.org/pdf/1809.01731.pdf) (2018)
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### Kernel methods and SVM
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* [Supervised learning with quantum enhanced feature spaces](https://arxiv.org/abs/1804.11326) (2018)
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* [Quantum Sparse Support Vector Machines](https://arxiv.org/abs/1902.01879) (2019)
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* [Sublinear quantum algorithms for training linear and kernel-based classifiers](https://arxiv.org/pdf/1904.02276.pdf) (2019)
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---
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## Continuous-variables quantum computing
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### Variational circuits
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* [Continuous-variable quantum neural networks](https://arxiv.org/abs/1806.06871) (2018)
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* [Machine learning method for state preparation and gate synthesis on photonic quantum computers](https://arxiv.org/abs/1807.10781) (2018)
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* [Near-deterministic production of universal quantum photonic gates enhanced by machine learning](https://arxiv.org/abs/1809.04680) (2018)
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### Kernel methods and SVM
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* [Quantum machine learning in feature Hilbert spaces](https://arxiv.org/1803.07128) (2018)
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