{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/quantum-machine-learning/papers/7","list_of":"/task/quantum-machine-learning","task":"Quantum Machine Learning","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":7,"pages_in_order":7,"rows_per_page":100,"rows":[601,699],"of":699,"counts":{"archive_papers_tagged":699,"with_a_code_link":140,"where_syntology_ran_a_sample":17,"not_listed_spam_title":0,"listed":699,"listed_where_code_ran":17,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":15,"every_run_a_failure_of_syntologys_instrument":2,"listed_with_a_run_with_no_instrument_failure":15,"listed_every_run_a_failure_of_syntologys_instrument":2,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/quantum-machine-learning","prev":"/task/quantum-machine-learning/papers/6","next":null,"papers":[{"url":null,"slug":"image-compression-and-classification-using-1","title":"Image Compression and Classification Using Qubits and Quantum Deep Learning","date":"2021-10-08","arxiv_id":"2110.05476","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-semi-supervised-learning-with-quantum","title":"Quantum Semi-Supervised Learning with Quantum Supremacy","date":"2021-10-05","arxiv_id":"2110.02343","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-machine-learning-for-finance","title":"Quantum Machine Learning for Finance","date":"2021-09-09","arxiv_id":"2109.04298","repositories_listed":0,"syntology":null},{"url":null,"slug":"iccad-special-session-paper-quantum-classical","title":"Quantum-Classical Hybrid Machine Learning for Image Classification (ICCAD Special Session Paper)","date":"2021-09-07","arxiv_id":"2109.02862","repositories_listed":0,"syntology":null},{"url":null,"slug":"recent-advances-for-quantum-classifiers","title":"Recent advances for quantum classifiers","date":"2021-08-30","arxiv_id":"2108.13421","repositories_listed":0,"syntology":null},{"url":null,"slug":"photonic-quantum-policy-learning-in-openai","title":"Photonic Quantum Policy Learning in OpenAI Gym","date":"2021-08-29","arxiv_id":"2108.12926","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-machine-learning-for-health-state","title":"Quantum Machine Learning for Health State Diagnosis and Prognostics","date":"2021-08-25","arxiv_id":"2108.12265","repositories_listed":0,"syntology":null},{"url":null,"slug":"new-trends-in-quantum-machine-learning","title":"New Trends in Quantum Machine Learning","date":"2021-08-22","arxiv_id":"2108.09664","repositories_listed":0,"syntology":null},{"url":null,"slug":"introduction-to-quantum-reinforcement","title":"Introduction to Quantum Reinforcement Learning: Theory and PennyLane-based Implementation","date":"2021-08-16","arxiv_id":"2108.06849","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-continual-learning-overcoming","title":"Quantum Continual Learning Overcoming Catastrophic Forgetting","date":"2021-08-05","arxiv_id":"2108.02786","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-topological-data-analysis-with-linear","title":"Quantum Topological Data Analysis with Linear Depth and Exponential Speedup","date":"2021-08-05","arxiv_id":"2108.02811","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybrid-quantum-classical-neural-network-for-1","title":"Hybrid Quantum-Classical Neural Network for Incident Detection","date":"2021-08-02","arxiv_id":"2108.01127","repositories_listed":0,"syntology":null},{"url":null,"slug":"sample-complexity-of-learning-quantum","title":"Sample Complexity of Learning Parametric Quantum Circuits","date":"2021-07-19","arxiv_id":"2107.09078","repositories_listed":0,"syntology":null},{"url":null,"slug":"fock-state-enhanced-expressivity-of-quantum","title":"Fock State-enhanced Expressivity of Quantum Machine Learning Models","date":"2021-07-12","arxiv_id":"2107.05224","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-machine-learning-fad-or-future","title":"Quantum Machine Learning: Fad or Future?","date":"2021-06-20","arxiv_id":"2106.10714","repositories_listed":0,"syntology":null},{"url":null,"slug":"exponential-error-convergence-in-data","title":"Exponential Error Convergence in Data Classification with Optimized Random Features: Acceleration by Quantum Machine Learning","date":"2021-06-16","arxiv_id":"2106.09028","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-design-of-quantum-feature-maps","title":"Automatic design of quantum feature maps","date":"2021-05-26","arxiv_id":"2105.12626","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-embedding-search-for-quantum-machine","title":"Quantum Embedding Search for Quantum Machine Learning","date":"2021-05-25","arxiv_id":"2105.11853","repositories_listed":0,"syntology":null},{"url":null,"slug":"structural-risk-minimization-for-quantum","title":"Structural risk minimization for quantum linear classifiers","date":"2021-05-12","arxiv_id":"2105.05566","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-machine-learning-for-classical-data","title":"Quantum Machine Learning For Classical Data","date":"2021-05-08","arxiv_id":"2105.03684","repositories_listed":0,"syntology":null},{"url":null,"slug":"higgs-analysis-with-quantum-classifiers","title":"Higgs analysis with quantum classifiers","date":"2021-04-15","arxiv_id":"2104.07692","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-machine-learning-for-power-system","title":"Noise-Resilient Quantum Machine Learning for Stability Assessment of Power Systems","date":"2021-04-10","arxiv_id":"2104.04855","repositories_listed":0,"syntology":null},{"url":null,"slug":"drug-discovery-approaches-using-quantum","title":"Drug Discovery Approaches using Quantum Machine Learning","date":"2021-04-01","arxiv_id":"2104.00746","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-understanding-the-power-of-quantum","title":"Towards understanding the power of quantum kernels in the NISQ era","date":"2021-03-31","arxiv_id":"2103.16774","repositories_listed":0,"syntology":null},{"url":null,"slug":"federated-quantum-machine-learning","title":"Federated Quantum Machine Learning","date":"2021-03-22","arxiv_id":"2103.12010","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-machine-learning-with-hqc","title":"Quantum Machine Learning with HQC Architectures using non-Classically Simulable Feature Maps","date":"2021-03-21","arxiv_id":"2103.11381","repositories_listed":0,"syntology":null},{"url":null,"slug":"diagrammatic-differentiation-for-quantum","title":"Diagrammatic Differentiation for Quantum Machine Learning","date":"2021-03-14","arxiv_id":"2103.07960","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-machine-learning-with-differential","title":"Quantum machine learning with differential privacy","date":"2021-03-10","arxiv_id":"2103.06232","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-cross-entropy-and-maximum-likelihood","title":"Quantum Cross Entropy and Maximum Likelihood Principle","date":"2021-02-23","arxiv_id":"2102.11887","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-in-quantum-machine-learning-a","title":"Generalization in Quantum Machine Learning: a Quantum Information Perspective","date":"2021-02-17","arxiv_id":"2102.08991","repositories_listed":0,"syntology":null},{"url":null,"slug":"universal-adversarial-examples-and","title":"Universal Adversarial Examples and Perturbations for Quantum Classifiers","date":"2021-02-15","arxiv_id":"2102.07788","repositories_listed":0,"syntology":null},{"url":null,"slug":"facial-expression-recognition-on-a-quantum","title":"Facial Expression Recognition on a Quantum Computer","date":"2021-02-09","arxiv_id":"2102.04823","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-machine-learning-with-adaptive-linear","title":"Quantum machine learning with adaptive linear optics","date":"2021-02-08","arxiv_id":"2102.04579","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-generative-models-via-quantum","title":"Enhancing Generative Models via Quantum Correlations","date":"2021-01-20","arxiv_id":"2101.08354","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybrid-quantum-classical-graph-convolutional","title":"Hybrid Quantum-Classical Graph Convolutional Network","date":"2021-01-15","arxiv_id":"2101.06189","repositories_listed":0,"syntology":null},{"url":null,"slug":"single-preparation-unsupervised-quantum","title":"Single-preparation unsupervised quantum machine learning: concepts and applications","date":"2021-01-05","arxiv_id":"2101.01442","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybrid-quantum-classical-stochastic-networks","title":"Hybrid Quantum-Classical Stochastic Networks with Boltzmann Layers","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-convolutional-neural-networks-for","title":"Quantum Convolutional Neural Networks for High Energy Physics Data Analysis","date":"2020-12-22","arxiv_id":"2012.12177","repositories_listed":0,"syntology":null},{"url":null,"slug":"residual-matrix-product-state-for-machine","title":"Residual Matrix Product State for Machine Learning","date":"2020-12-22","arxiv_id":"2012.11841","repositories_listed":0,"syntology":null},{"url":null,"slug":"variational-quantum-cloning-improving","title":"Variational Quantum Cloning: Improving Practicality for Quantum Cryptanalysis","date":"2020-12-21","arxiv_id":"2012.11424","repositories_listed":0,"syntology":null},{"url":null,"slug":"practical-application-improvement-to-quantum","title":"Practical application improvement to Quantum SVM: theory to practice","date":"2020-12-14","arxiv_id":"2012.07725","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybrid-quantum-classical-classifier-based-on","title":"Hybrid quantum-classical classifier based on tensor network and variational quantum circuit","date":"2020-11-30","arxiv_id":"2011.14651","repositories_listed":0,"syntology":null},{"url":null,"slug":"prospects-and-challenges-of-quantum-finance","title":"Prospects and challenges of quantum finance","date":"2020-11-12","arxiv_id":"2011.06492","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-classification-via-quantum-machine","title":"Image Classification via Quantum Machine Learning","date":"2020-11-03","arxiv_id":"2011.02831","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-shift-to-6g-communications-vision-and","title":"The Shift to 6G Communications: Vision and Requirements","date":"2020-10-15","arxiv_id":"2010.07993","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimal-provable-robustness-of-quantum","title":"Optimal Provable Robustness of Quantum Classification via Quantum Hypothesis Testing","date":"2020-09-21","arxiv_id":"2009.10064","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-discriminator-for-binary","title":"Quantum Discriminator for Binary Classification","date":"2020-09-02","arxiv_id":"2009.01235","repositories_listed":0,"syntology":null},{"url":null,"slug":"universal-approximation-property-of-quantum","title":"Universal Approximation Property of Quantum Machine Learning Models in Quantum-Enhanced Feature Spaces","date":"2020-09-01","arxiv_id":"2009.00298","repositories_listed":0,"syntology":null},{"url":null,"slug":"robustness-verification-of-quantum-machine","title":"Robustness Verification of Quantum Classifiers","date":"2020-08-17","arxiv_id":"2008.07230","repositories_listed":0,"syntology":null},{"url":null,"slug":"supervised-learning-using-a-dressed-quantum","title":"Supervised Learning Using a Dressed Quantum Network with \"Super Compressed Encoding\": Algorithm and Quantum-Hardware-Based Implementation","date":"2020-07-20","arxiv_id":"2007.10242","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-ensemble-of-trained-classifiers","title":"Quantum ensemble of trained classifiers","date":"2020-07-18","arxiv_id":"2007.09293","repositories_listed":0,"syntology":null},{"url":null,"slug":"reformulation-of-the-no-free-lunch-theorem","title":"Reformulation of the No-Free-Lunch Theorem for Entangled Data Sets","date":"2020-07-09","arxiv_id":"2007.04900","repositories_listed":0,"syntology":null},{"url":null,"slug":"classification-with-quantum-machine-learning","title":"Classification with Quantum Machine Learning: A Survey","date":"2020-06-22","arxiv_id":"2006.12270","repositories_listed":0,"syntology":null},{"url":null,"slug":"high-dimensional-similarity-search-with","title":"High-Dimensional Similarity Search with Quantum-Assisted Variational Autoencoder","date":"2020-06-13","arxiv_id":"2006.07680","repositories_listed":0,"syntology":null},{"url":null,"slug":"experimental-demonstration-of-a-quantum","title":"Noise robustness and experimental demonstration of a quantum generative adversarial network for continuous distributions","date":"2020-06-02","arxiv_id":"2006.01976","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-natural-language-processing-on-near","title":"Quantum Natural Language Processing on Near-Term Quantum Computers","date":"2020-05-08","arxiv_id":"2005.04147","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-quantum-advantage-for-topological","title":"Towards quantum advantage via topological data analysis","date":"2020-05-06","arxiv_id":"2005.02607","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-machine-learning-and-quantum","title":"Quantum machine learning and quantum biomimetics: A perspective","date":"2020-04-25","arxiv_id":"2004.12076","repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-quantum-algorithm-for-learning-with","title":"Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions","date":"2020-04-22","arxiv_id":"2004.10756","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-data-encodings-for-quantum-classifiers","title":"Robust data encodings for quantum classifiers","date":"2020-03-03","arxiv_id":"2003.01695","repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-quantum-learning-with-statistical","title":"Statistical Limits of Supervised Quantum Learning","date":"2020-01-28","arxiv_id":"2001.10477","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-machine-learning-algorithm-for","title":"Quantum Machine Learning Algorithm for Knowledge Graphs","date":"2020-01-04","arxiv_id":"2001.01077","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-adversarial-machine-learning","title":"Quantum Adversarial Machine Learning","date":"2019-12-31","arxiv_id":"2001.00030","repositories_listed":0,"syntology":null},{"url":null,"slug":"solving-machine-learning-optimization","title":"Solving machine learning optimization problems using quantum computers","date":"2019-11-17","arxiv_id":"1911.08587","repositories_listed":0,"syntology":null},{"url":null,"slug":"sampling-based-sublinear-low-rank-matrix","title":"Sampling-based sublinear low-rank matrix arithmetic framework for dequantizing quantum machine learning","date":"2019-10-14","arxiv_id":"1910.06151","repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-learning-phase-transitions-with-a","title":"Machine Learning Phase Transitions with a Quantum Processor","date":"2019-06-24","arxiv_id":"1906.10155","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantized-three-ion-channel-neuron-model-for","title":"Quantized Three-Ion-Channel Neuron Model for Neural Action Potentials","date":"2019-06-16","arxiv_id":"1906.07570","repositories_listed":0,"syntology":null},{"url":null,"slug":"190410508","title":"Quantum-Inspired Computing: Can it be a Microscopic Computing Model of the Brain?","date":"2019-04-11","arxiv_id":"1904.10508","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-born-supremacy-quantum-advantage-and","title":"The Born Supremacy: Quantum Advantage and Training of an Ising Born Machine","date":"2019-04-03","arxiv_id":"1904.02214","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-speedup-in-adaptive-boosting-of","title":"Quantum Speedup in Adaptive Boosting of Binary Classification","date":"2019-02-03","arxiv_id":"1902.00869","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-algorithms-for-feedforward-neural","title":"Quantum algorithms for feedforward neural networks","date":"2018-12-07","arxiv_id":"1812.03089","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-amalgamation-of-classical-and-quantum","title":"An Amalgamation of Classical and Quantum Machine Learning For the Classification of Adenocarcinoma and Squamous Cell Carcinoma Patients","date":"2018-10-29","arxiv_id":"1810.11959","repositories_listed":0,"syntology":null},{"url":null,"slug":"topographic-representation-for-quantum","title":"Topographic Representation for Quantum Machine Learning","date":"2018-10-13","arxiv_id":"1810.06992","repositories_listed":0,"syntology":null},{"url":null,"slug":"smooth-structured-prediction-using-quantum","title":"Quantum Algorithms for Structured Prediction","date":"2018-09-11","arxiv_id":"1809.04091","repositories_listed":0,"syntology":null},{"url":null,"slug":"nonlinear-regression-based-on-a-hybrid","title":"Nonlinear regression based on a hybrid quantum computer","date":"2018-08-29","arxiv_id":"1808.09607","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantized-hodgkin-huxley-model-for-quantum","title":"Quantized Single-Ion-Channel Hodgkin-Huxley Model for Quantum Neurons","date":"2018-07-27","arxiv_id":"1807.10698","repositories_listed":0,"syntology":null},{"url":null,"slug":"supervised-learning-with-generalized-tensor","title":"From probabilistic graphical models to generalized tensor networks for supervised learning","date":"2018-06-15","arxiv_id":"1806.05964","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-classification-of-the-mnist-dataset","title":"Quantum classification of the MNIST dataset with Slow Feature Analysis","date":"2018-05-22","arxiv_id":"1805.08837","repositories_listed":0,"syntology":null},{"url":null,"slug":"universal-discriminative-quantum-neural","title":"Universal discriminative quantum neural networks","date":"2018-05-22","arxiv_id":"1805.08654","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-generative-adversarial-networks","title":"Quantum generative adversarial networks","date":"2018-04-23","arxiv_id":"1804.08641","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-machine-learning-matrix-product","title":"Quantum Machine Learning Tensor Network States","date":"2018-04-06","arxiv_id":"1804.02398","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-quantum-machine-learning-with-tensor","title":"Towards Quantum Machine Learning with Tensor Networks","date":"2018-03-30","arxiv_id":"1803.11537","repositories_listed":0,"syntology":null},{"url":null,"slug":"demonstration-of-envariance-and-parity","title":"Efficient and Effective Quantum Compiling for Entanglement-based Machine Learning on IBM Q Devices","date":"2018-01-08","arxiv_id":"1801.02363","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-artificial-life-in-an-ibm-quantum","title":"Quantum Artificial Life in an IBM Quantum Computer","date":"2017-11-26","arxiv_id":"1711.09442","repositories_listed":0,"syntology":null},{"url":null,"slug":"hardening-quantum-machine-learning-against","title":"Hardening Quantum Machine Learning Against Adversaries","date":"2017-11-17","arxiv_id":"1711.06652","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-efficient-quantum-algorithm-for-generative","title":"An efficient quantum algorithm for generative machine learning","date":"2017-11-06","arxiv_id":"1711.02038","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhanced-quantum-synchronization-via-quantum","title":"Enhanced Quantum Synchronization via Quantum Machine Learning","date":"2017-09-25","arxiv_id":"1709.08519","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-autoencoders-via-quantum-adders-with","title":"Quantum autoencoders via quantum adders with genetic algorithms","date":"2017-09-21","arxiv_id":"1709.07409","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-machine-learning-a-classical","title":"Quantum machine learning: a classical perspective","date":"2017-07-26","arxiv_id":"1707.08561","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-ensembles-of-quantum-classifiers","title":"Quantum ensembles of quantum classifiers","date":"2017-04-07","arxiv_id":"1704.02146","repositories_listed":0,"syntology":null},{"url":null,"slug":"basic-protocols-in-quantum-reinforcement","title":"Basic protocols in quantum reinforcement learning with superconducting circuits","date":"2017-01-18","arxiv_id":"1701.05131","repositories_listed":0,"syntology":null},{"url":null,"slug":"supervised-quantum-learning-without","title":"Supervised Quantum Learning without Measurements","date":"2016-12-16","arxiv_id":"1612.05535","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-machine-learning","title":"Quantum Machine Learning","date":"2016-11-28","arxiv_id":"1611.09347","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-enhanced-machine-learning","title":"Quantum-enhanced machine learning","date":"2016-10-26","arxiv_id":"1610.08251","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-neural-machine-learning","title":"Quantum Neural Machine Learning - Backpropagation and Dynamics","date":"2016-09-22","arxiv_id":"1609.06935","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-recommendation-systems","title":"Quantum Recommendation Systems","date":"2016-09-22","arxiv_id":"1603.08675","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-machine-learning-with-glow-for","title":"Quantum machine learning with glow for episodic tasks and decision games","date":"2016-01-27","arxiv_id":"1601.07358","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-learnability-of-unknown-quantum","title":"The Learnability of Unknown Quantum Measurements","date":"2015-01-03","arxiv_id":"1501.00559","repositories_listed":0,"syntology":null},{"url":null,"slug":"simulating-a-perceptron-on-a-quantum-computer","title":"Simulating a perceptron on a quantum computer","date":"2014-12-11","arxiv_id":"1412.3635","repositories_listed":0,"syntology":null}],"record_sha256":"d437c94b6a290f5e52a82f483aca4bf0dd62e58160aaf43a3036f44024250c17","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}