{"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/experimental-design/papers/6","list_of":"/task/experimental-design","task":"Experimental Design","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":6,"pages_in_order":7,"rows_per_page":100,"rows":[501,600],"of":688,"counts":{"archive_papers_tagged":688,"with_a_code_link":197,"where_syntology_ran_a_sample":51,"not_listed_spam_title":0,"listed":688,"listed_where_code_ran":51,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":43,"every_run_a_failure_of_syntologys_instrument":8,"listed_with_a_run_with_no_instrument_failure":43,"listed_every_run_a_failure_of_syntologys_instrument":8,"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/experimental-design","prev":"/task/experimental-design/papers/5","next":"/task/experimental-design/papers/7","papers":[{"url":null,"slug":"a-hybrid-gradient-method-to-designing","title":"A Hybrid Gradient Method to Designing Bayesian Experiments for Implicit Models","date":"2021-03-14","arxiv_id":"2103.08594","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-scalable-gradient-free-method-for-bayesian","title":"A Scalable Gradient-Free Method for Bayesian Experimental Design with Implicit Models","date":"2021-03-14","arxiv_id":"2103.08026","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-simulation-based-test-of-identifiability","title":"SBI: A Simulation-Based Test of Identifiability for Bayesian Causal Inference","date":"2021-02-23","arxiv_id":"2102.11761","repositories_listed":0,"syntology":null},{"url":null,"slug":"formation-of-social-ties-influences-food","title":"Formation of Social Ties Influences Food Choice: A Campus-Wide Longitudinal Study","date":"2021-02-17","arxiv_id":"2102.08755","repositories_listed":0,"syntology":null},{"url":null,"slug":"demarcating-endogenous-and-exogenous-opinion","title":"Demarcating Endogenous and Exogenous Opinion Dynamics: An Experimental Design Approach","date":"2021-02-11","arxiv_id":"2102.05954","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-models-of-model-predictive","title":"Learning Models of Model Predictive Controllers using Gradient Data","date":"2021-02-03","arxiv_id":"2102.02173","repositories_listed":0,"syntology":null},{"url":null,"slug":"comparing-hundreds-of-machine-learning","title":"Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark","date":"2021-02-01","arxiv_id":"2102.01130","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-methodology-for-the-development-of-rl-based","title":"A Methodology for the Development of RL-Based Adaptive Traffic Signal Controllers","date":"2021-01-24","arxiv_id":"2101.09614","repositories_listed":0,"syntology":null},{"url":null,"slug":"differential-euler-designing-a-neural-network","title":"Differential Euler: Designing a Neural Network approximator to solve the Chaotic Three Body Problem","date":"2021-01-21","arxiv_id":"2101.08486","repositories_listed":0,"syntology":null},{"url":null,"slug":"stochastic-learning-approach-to-binary","title":"Stochastic Learning Approach to Binary Optimization for Optimal Design of Experiments","date":"2021-01-15","arxiv_id":"2101.05958","repositories_listed":0,"syntology":null},{"url":null,"slug":"data-driven-peakon-and-periodic-peakon","title":"Data-driven peakon and periodic peakon travelling wave solutions of some nonlinear dispersive equations via deep learning","date":"2021-01-12","arxiv_id":"2101.04371","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-tinkering-to-engineering-measurements-in","title":"From Tinkering to Engineering: Measurements in Tensorflow Playground","date":"2021-01-11","arxiv_id":"2101.04141","repositories_listed":0,"syntology":null},{"url":null,"slug":"maximizing-information-gain-for-the","title":"Maximizing Information Gain for the Characterization of Biomolecular Circuits","date":"2021-01-08","arxiv_id":"2101.02924","repositories_listed":0,"syntology":null},{"url":null,"slug":"just-how-toxic-is-data-poisoning-a-benchmark","title":"Just How Toxic is Data Poisoning? A Benchmark for Backdoor and Data Poisoning Attacks","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-collision-free-latent-space-for","title":"Learning Collision-free Latent Space for Bayesian Optimization","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"near-optimal-glimpse-sequences-for-training","title":"Near-Optimal Glimpse Sequences for Training Hard Attention Neural Networks","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"predicting-the-impact-of-dataset-composition","title":"Predicting the impact of dataset composition on model performance","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"the-wealth-of-nations-and-the-health-of","title":"The wealth of nations and the health of populations: A quasi-experimental design of the impact of sovereign debt crises on child mortality","date":"2020-12-29","arxiv_id":"2012.14941","repositories_listed":0,"syntology":null},{"url":null,"slug":"refined-bounds-for-randomized-experimental","title":"Refined bounds for randomized experimental design","date":"2020-12-22","arxiv_id":"2012.15726","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalized-chernoff-sampling-for-active","title":"Chernoff Sampling for Active Testing and Extension to Active Regression","date":"2020-12-15","arxiv_id":"2012.08073","repositories_listed":0,"syntology":null},{"url":null,"slug":"do-competent-women-receive-unfavorable","title":"Are Men Less Generous to a Smarter Woman? Evidence from a Dictator Game Experiment","date":"2020-12-08","arxiv_id":"2012.04591","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-fake-news-effect-experimentally","title":"The Fake News Effect: Experimentally Identifying Motivated Reasoning Using Trust in News","date":"2020-12-03","arxiv_id":"2012.01663","repositories_listed":0,"syntology":null},{"url":null,"slug":"sequential-bayesian-experimental-design-with","title":"Sequential Bayesian Experimental Design with Variable Cost Structure","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"twenty-years-of-confusion-in-human-evaluation","title":"Twenty Years of Confusion in Human Evaluation: NLG Needs Evaluation Sheets and Standardised Definitions","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"safe-model-based-design-of-experiments-using","title":"Safe model-based design of experiments using Gaussian processes","date":"2020-11-19","arxiv_id":"2011.10009","repositories_listed":0,"syntology":null},{"url":null,"slug":"policy-choice-in-experiments-with-unknown","title":"Policy design in experiments with unknown interference","date":"2020-11-16","arxiv_id":"2011.08174","repositories_listed":0,"syntology":null},{"url":null,"slug":"identifying-causal-effects-in-experiments","title":"Identifying Causal Effects in Experiments with Spillovers and Non-compliance","date":"2020-11-13","arxiv_id":"2011.07051","repositories_listed":0,"syntology":null},{"url":null,"slug":"influence-of-event-duration-on-automatic","title":"Influence of Event Duration on Automatic Wheeze Classification","date":"2020-11-04","arxiv_id":"2011.02874","repositories_listed":0,"syntology":null},{"url":null,"slug":"experimental-design-for-regret-minimization","title":"Experimental Design for Regret Minimization in Linear Bandits","date":"2020-11-01","arxiv_id":"2011.00576","repositories_listed":0,"syntology":null},{"url":null,"slug":"grammaticality-and-language-modelling","title":"Grammaticality and Language Modelling","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-local-search-framework-for-experimental","title":"A Local Search Framework for Experimental Design","date":"2020-10-29","arxiv_id":"2010.15805","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-evaluation-protocol-for-generative","title":"An Evaluation Protocol for Generative Conversational Systems","date":"2020-10-24","arxiv_id":"2010.12741","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-sensitivity-of-icf-outputs-to","title":"Exploring Sensitivity of ICF Outputs to Design Parameters in Experiments Using Machine Learning","date":"2020-10-08","arxiv_id":"2010.04254","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-primer-on-model-guided-exploration-of","title":"A primer on model-guided exploration of fitness landscapes for biological sequence design","date":"2020-10-04","arxiv_id":"2010.10614","repositories_listed":0,"syntology":null},{"url":null,"slug":"experimental-design-for-overparameterized","title":"Experimental Design for Overparameterized Learning with Application to Single Shot Deep Active Learning","date":"2020-09-27","arxiv_id":"2009.12820","repositories_listed":0,"syntology":null},{"url":null,"slug":"stochastic-revealed-preferences-with","title":"Stochastic Revealed Preferences with Measurement Error","date":"2020-09-18","arxiv_id":"1810.05287","repositories_listed":0,"syntology":null},{"url":null,"slug":"comparison-lift-bandit-based-experimentation","title":"Comparison Lift: Bandit-based Experimentation System for Online Advertising","date":"2020-09-16","arxiv_id":"2009.07899","repositories_listed":0,"syntology":null},{"url":null,"slug":"sparse-polynomial-chaos-expansions-solvers","title":"Automatic selection of basis-adaptive sparse polynomial chaos expansions for engineering applications","date":"2020-09-10","arxiv_id":"2009.04800","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-adaptive-random-experiment-design-method","title":"An adaptive random experiment design method for engineering experiment","date":"2020-08-27","arxiv_id":"2008.13581","repositories_listed":0,"syntology":null},{"url":null,"slug":"integrated-cutting-and-packing-heterogeneous","title":"Integrated Cutting and Packing Heterogeneous Precast Beams Multiperiod Production Planning Problem","date":"2020-08-25","arxiv_id":"2008.11303","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-new-perspective-on-pool-based-active-1","title":"A New Perspective on Pool-Based Active Classification and False-Discovery Control","date":"2020-08-14","arxiv_id":"2008.06555","repositories_listed":0,"syntology":null},{"url":null,"slug":"online-graph-completion-multivariate-signal-1","title":"Online Graph Completion: Multivariate Signal Recovery in Computer Vision","date":"2020-08-12","arxiv_id":"2008.05060","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimal-bayesian-experimental-design-for","title":"Optimal Bayesian experimental design for subsurface flow problems","date":"2020-08-10","arxiv_id":"2008.03989","repositories_listed":0,"syntology":null},{"url":null,"slug":"are-visual-explanations-useful-a-case-study","title":"Are Visual Explanations Useful? A Case Study in Model-in-the-Loop Prediction","date":"2020-07-23","arxiv_id":"2007.12248","repositories_listed":0,"syntology":null},{"url":null,"slug":"experimental-design-for-bathymetry-editing","title":"Experimental Design for Bathymetry Editing","date":"2020-07-15","arxiv_id":"2007.07495","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-importance-of-block-randomisation-when","title":"On the importance of block randomisation when designing proteomics experiments","date":"2020-07-13","arxiv_id":"2007.06336","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimal-experimental-design-for-uncertain","title":"Optimal Experimental Design for Uncertain Systems Based on Coupled Differential Equations","date":"2020-07-12","arxiv_id":"2007.06117","repositories_listed":0,"syntology":null},{"url":null,"slug":"gamification-of-pure-exploration-for-linear","title":"Gamification of Pure Exploration for Linear Bandits","date":"2020-07-02","arxiv_id":"2007.00953","repositories_listed":0,"syntology":null},{"url":null,"slug":"syntaxgym-an-online-platform-for-targeted","title":"SyntaxGym: An Online Platform for Targeted Evaluation of Language Models","date":"2020-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"recovery-of-sparse-signals-from-a-mixture-of","title":"Recovery of Sparse Signals from a Mixture of Linear Samples","date":"2020-06-29","arxiv_id":"2006.16406","repositories_listed":0,"syntology":null},{"url":null,"slug":"show-me-the-way-intrinsic-motivation-from","title":"Show me the Way: Intrinsic Motivation from Demonstrations","date":"2020-06-23","arxiv_id":"2006.12917","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-empirical-process-approach-to-the-union","title":"An Empirical Process Approach to the Union Bound: Practical Algorithms for Combinatorial and Linear Bandits","date":"2020-06-21","arxiv_id":"2006.11685","repositories_listed":0,"syntology":null},{"url":null,"slug":"claimed-a-classification-incorporated-minimum","title":"CLAIMED: A CLAssification-Incorporated Minimum Energy Design to explore a multivariate response surface with feasibility constraints","date":"2020-06-09","arxiv_id":"2006.05021","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-criminality-from-face-illusion","title":"The Criminality From Face Illusion","date":"2020-06-06","arxiv_id":"2006.03895","repositories_listed":0,"syntology":null},{"url":null,"slug":"generating-artificial-outliers-in-the-absence","title":"Generating Artificial Outliers in the Absence of Genuine Ones -- a Survey","date":"2020-06-05","arxiv_id":"2006.03646","repositories_listed":0,"syntology":null},{"url":null,"slug":"batch-greedy-maximization-of-non-submodular","title":"Batch greedy maximization of non-submodular functions: Guarantees and applications to experimental design","date":"2020-06-03","arxiv_id":"2006.04554","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimal-experiment-design-for-ac-power","title":"Optimal Experiment Design for AC Power Systems Admittance Estimation","date":"2020-05-11","arxiv_id":"1912.09017","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-optimality-of-randomization-in","title":"On the Optimality of Randomization in Experimental Design: How to Randomize for Minimax Variance and Design-Based Inference","date":"2020-05-06","arxiv_id":"2005.03151","repositories_listed":0,"syntology":null},{"url":null,"slug":"cheese-a-corpus-of-face-to-face-french","title":"``Cheese!'': a Corpus of Face-to-face French Interactions. A Case Study for Analyzing Smiling and Conversational Humor","date":"2020-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"coupled-differentiation-and-division-of","title":"Coupled differentiation and division of embryonic stem cells inferred from clonal snapshots","date":"2020-04-27","arxiv_id":"2004.12902","repositories_listed":0,"syntology":null},{"url":null,"slug":"maximizing-determinants-under-matroid","title":"Maximizing Determinants under Matroid Constraints","date":"2020-04-16","arxiv_id":"2004.07886","repositories_listed":0,"syntology":null},{"url":null,"slug":"gravitational-wave-detection-and-information","title":"Gravitational Wave Detection and Information Extraction via Neural Networks","date":"2020-03-22","arxiv_id":"2003.09995","repositories_listed":0,"syntology":null},{"url":null,"slug":"experimental-design-under-network","title":"Experimental Design under Network Interference","date":"2020-03-18","arxiv_id":"2003.08421","repositories_listed":0,"syntology":null},{"url":null,"slug":"memory-efficient-learning-for-large-scale-1","title":"Memory-efficient Learning for Large-scale Computational Imaging","date":"2020-03-11","arxiv_id":"2003.05551","repositories_listed":0,"syntology":null},{"url":null,"slug":"incorporating-expert-prior-knowledge-into","title":"Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling","date":"2020-02-26","arxiv_id":"2002.11256","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptive-experimental-design-for-efficient","title":"Efficient Adaptive Experimental Design for Average Treatment Effect Estimation","date":"2020-02-13","arxiv_id":"2002.05308","repositories_listed":0,"syntology":null},{"url":null,"slug":"alpine-active-link-prediction-using-network","title":"ALPINE: Active Link Prediction using Network Embedding","date":"2020-02-04","arxiv_id":"2002.01227","repositories_listed":0,"syntology":null},{"url":null,"slug":"convolutional-neural-networks-as-summary","title":"Convolutional Neural Networks as Summary Statistics for Approximate Bayesian Computation","date":"2020-01-31","arxiv_id":"2001.11760","repositories_listed":0,"syntology":null},{"url":null,"slug":"convergence-guarantees-for-gaussian-process","title":"Convergence Guarantees for Gaussian Process Means With Misspecified Likelihoods and Smoothness","date":"2020-01-29","arxiv_id":"2001.10818","repositories_listed":0,"syntology":null},{"url":null,"slug":"memory-efficient-learning-for-large-scale","title":"Memory-efficient Learning for Large-scale Computational Imaging -- NeurIPS deep inverse workshop","date":"2019-12-11","arxiv_id":"1912.05098","repositories_listed":0,"syntology":null},{"url":null,"slug":"effect-of-imbalanced-datasets-on-security-of","title":"Effect of Imbalanced Datasets on Security of Industrial IoT Using Machine Learning","date":"2019-12-02","arxiv_id":"1912.02651","repositories_listed":0,"syntology":null},{"url":null,"slug":"sample-efficient-active-learning-of-causal","title":"Sample Efficient Active Learning of Causal Trees","date":"2019-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"iterative-peptide-modeling-with-active","title":"Investigating Active Learning and Meta-Learning for Iterative Peptide Design","date":"2019-11-20","arxiv_id":"1911.09103","repositories_listed":0,"syntology":null},{"url":null,"slug":"replication-based-emulation-of-the-response","title":"Replication-based emulation of the response distribution of stochastic simulators using generalized lambda distributions","date":"2019-11-20","arxiv_id":"1911.09067","repositories_listed":0,"syntology":null},{"url":null,"slug":"incentive-compatible-active-learning","title":"Incentive Compatible Active Learning","date":"2019-11-12","arxiv_id":"1911.05171","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptivity-in-adaptive-submodularity","title":"Adaptivity in Adaptive Submodularity","date":"2019-11-09","arxiv_id":"1911.03620","repositories_listed":0,"syntology":null},{"url":null,"slug":"connecting-exciton-diffusion-with-surface","title":"A QMC-deep learning method for diffusivity estimation in random domains","date":"2019-10-31","arxiv_id":"1910.14209","repositories_listed":0,"syntology":null},{"url":null,"slug":"bayesian-experimental-design-for-finding","title":"Bayesian Experimental Design for Finding Reliable Level Set under Input Uncertainty","date":"2019-10-26","arxiv_id":"1910.12043","repositories_listed":0,"syntology":null},{"url":null,"slug":"grammatical-gender-neo-whorfianism-and-word","title":"Grammatical Gender, Neo-Whorfianism, and Word Embeddings: A Data-Driven Approach to Linguistic Relativity","date":"2019-10-22","arxiv_id":"1910.09729","repositories_listed":0,"syntology":null},{"url":null,"slug":"genomic-variety-prediction-via-bayesian","title":"Genomic variety prediction via Bayesian nonparametrics","date":"2019-10-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"batch-simulations-and-uncertainty","title":"Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation","date":"2019-10-14","arxiv_id":"1910.06121","repositories_listed":0,"syntology":null},{"url":null,"slug":"bayesian-optimization-using-pseudo-points","title":"Bayesian Optimization using Pseudo-Points","date":"2019-10-12","arxiv_id":"1910.05484","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-objective-evolutionary-algorithms-are","title":"Multi-objective Evolutionary Algorithms are Still Good: Maximizing Monotone Approximately Submodular Minus Modular Functions","date":"2019-10-12","arxiv_id":"1910.05492","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimal-experimental-design-via-bayesian","title":"Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks","date":"2019-10-09","arxiv_id":"1910.03962","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-difficulty-of-warm-starting-neural-1","title":"On The Difficulty of Warm-Starting Neural Network Training","date":"2019-09-25","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"190909859","title":"DECoVaC: Design of Experiments with Controlled Variability Components","date":"2019-09-21","arxiv_id":"1909.09859","repositories_listed":0,"syntology":null},{"url":null,"slug":"lexical-quantile-based-text-complexity","title":"Lexical Quantile-Based Text Complexity Measure","date":"2019-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"online-inference-for-advertising-auctions","title":"Online Causal Inference for Advertising in Real-Time Bidding Auctions","date":"2019-08-22","arxiv_id":"1908.08600","repositories_listed":0,"syntology":null},{"url":null,"slug":"sequential-computer-experimental-design-for","title":"Sequential Computer Experimental Design for Estimating an Extreme Probability or Quantile","date":"2019-08-14","arxiv_id":"1908.05357","repositories_listed":0,"syntology":null},{"url":null,"slug":"accelerating-experimental-design-by","title":"Accelerating Experimental Design by Incorporating Experimenter Hunches","date":"2019-07-22","arxiv_id":"1907.09065","repositories_listed":0,"syntology":null},{"url":null,"slug":"output-weighted-optimal-sampling-for-bayesian","title":"Output-weighted optimal sampling for Bayesian regression and rare event statistics using few samples","date":"2019-07-17","arxiv_id":"1907.07552","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multifactorial-evaluation-framework-for","title":"A multifactorial evaluation framework for gene regulatory network reconstruction","date":"2019-06-28","arxiv_id":"1906.12243","repositories_listed":0,"syntology":null},{"url":null,"slug":"gift-contagion-in-online-groups-evidence-from","title":"Gift Contagion in Online Groups: Evidence From Virtual Red Packets","date":"2019-06-24","arxiv_id":"1906.09698","repositories_listed":0,"syntology":null},{"url":null,"slug":"principled-frameworks-for-evaluating-ethics","title":"Principled Frameworks for Evaluating Ethics in NLP Systems","date":"2019-06-14","arxiv_id":"1906.06425","repositories_listed":0,"syntology":null},{"url":null,"slug":"near-optimal-glimpse-sequences-for-improved","title":"Near-Optimal Glimpse Sequences for Improved Hard Attention Neural Network Training","date":"2019-06-13","arxiv_id":"1906.05462","repositories_listed":0,"syntology":null},{"url":null,"slug":"estimating-and-inferring-the-maximum-degree","title":"Estimating and Inferring the Maximum Degree of Stimulus-Locked Time-Varying Brain Connectivity Networks","date":"2019-05-28","arxiv_id":"1905.11588","repositories_listed":0,"syntology":null},{"url":null,"slug":"batched-stochastic-bayesian-optimization-via","title":"Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design","date":"2019-04-17","arxiv_id":"1904.08102","repositories_listed":0,"syntology":null},{"url":null,"slug":"data-driven-design-for-fourier-ptychographic","title":"Data-Driven Design for Fourier Ptychographic Microscopy","date":"2019-04-08","arxiv_id":"1904.04175","repositories_listed":0,"syntology":null},{"url":null,"slug":"assessment-of-faster-r-cnn-in-man-machine","title":"Assessment of Faster R-CNN in Man-Machine collaborative search","date":"2019-04-04","arxiv_id":"1904.02805","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comprehensive-comparison-of-unsupervised","title":"A Comparative Study for Unsupervised Network Representation Learning","date":"2019-03-19","arxiv_id":"1903.07902","repositories_listed":0,"syntology":null}],"record_sha256":"b047f264bf2355fda79052972a448c0c757858812caa904255bb825a20feea33","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}