Paper Citation Record · LEDGER

Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 46 inbound Pith citation observations for arXiv:0912.3995.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
0912.3995 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 46 of 46 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:34:10.689747Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

1053
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 6b4df3c6-da89-4011-b682-d99c47ddd0aa · inbound

A Bandit Approach to Posterior Dialog Orchestration Under a Budget cites this paper.

A Bandit Approach to Posterior Dialog Orchestration Under a Budget Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-05-25T18:36:07.916755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b142b139-314e-41bd-92be-51a195e9b98d · inbound

Data-Centric Mixed-Variable Bayesian Optimization For Materials Design cites this paper.

Data-Centric Mixed-Variable Bayesian Optimization For Materials Design Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-05-25T08:55:33.006925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c007b392-1a8f-4030-88b9-921b5462768a · inbound

Composite Bayesian Optimization In Function Spaces Using NEON -- Neural Epistemic Operator Networks cites this paper.

Composite Bayesian Optimization In Function Spaces Using NEON -- Neural Epistemic Operator Networks Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 36

Resolution: metadata mismatch; local_arxiv, observed 2026-05-24T02:23:46.035506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ae8a0753-f82b-417a-86bd-6c51defefe32 · inbound

Contextual Bandit Optimization with Pre-Trained Neural Networks cites this paper.

Contextual Bandit Optimization with Pre-Trained Neural Networks Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-10T21:34:10.689747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ab0a07e-f1b6-446b-a570-07c382712bbc · inbound

On the convergence rate of noisy Bayesian Optimization with Expected Improvement cites this paper.

On the convergence rate of noisy Bayesian Optimization with Expected Improvement Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T20:17:53.331482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62c1c0dd-b355-4f90-b827-76753536adef · inbound

Bayesian Optimization for Building Social-Influence-Free Consensus cites this paper.

Bayesian Optimization for Building Social-Influence-Free Consensus Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-08T13:41:36.465694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eacb2da3-ec29-45a0-8f32-f08cff2c9b9f · inbound

Quick-Draw Bandits: Quickly Optimizing in Nonstationary Environments with Extremely Many Arms cites this paper.

Quick-Draw Bandits: Quickly Optimizing in Nonstationary Environments with Extremely Many Arms Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T12:24:43.179280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec44e9ae-76ef-4c86-9c7a-0db1d763d025 · inbound

Bayesian Optimization over Bounded Domains with the Beta Product Kernel cites this paper.

Bayesian Optimization over Bounded Domains with the Beta Product Kernel Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-06T23:57:09.113253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be21e6f9-4087-4b92-b1ff-9a6fb0a1aa21 · inbound

AI Space Cortex: An Experimental System for Future Era Space Exploration cites this paper.

AI Space Cortex: An Experimental System for Future Era Space Exploration Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T19:06:22.337623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36a703ac-d384-44f8-a73f-28f6dadd0e0c · inbound

Cost-aware Stopping for Bayesian Optimization cites this paper.

Cost-aware Stopping for Bayesian Optimization Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 2012

Resolution: unresolved; no resolver link, observed 2026-08-06T16:56:50.000771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28e5e993-ed35-4511-afb0-f62ce70397a9 · inbound

Information Preserving Line Search via Bayesian Optimization cites this paper.

Information Preserving Line Search via Bayesian Optimization Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T15:37:30.585911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1714a8df-48e1-48fd-996a-792ade6e8223 · inbound

Multi-fidelity Bayesian Data-Driven Design of Energy Absorbing Spinodoid Cellular Structures cites this paper.

Multi-fidelity Bayesian Data-Driven Design of Energy Absorbing Spinodoid Cellular Structures Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-06T14:25:55.275595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a19a6431-8d5f-44b9-91e4-db0924400dda · inbound

Efficient Human-Aware Task Allocation for Multi-Robot Systems in Shared Environments cites this paper.

Efficient Human-Aware Task Allocation for Multi-Robot Systems in Shared Environments Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T15:34:31.710660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7adc4bc-0f57-4f45-b9c7-0a375f2f40dd · inbound

Directed Evolution of Proteins via Bayesian Optimization in Embedding Space cites this paper.

Directed Evolution of Proteins via Bayesian Optimization in Embedding Space Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T05:45:29.392823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb16fc3a-2db7-43aa-9df7-10834ddb5489 · inbound

Uncertainty-Aware Offline Data-Driven Multi-Objective Optimization cites this paper.

Uncertainty-Aware Offline Data-Driven Multi-Objective Optimization Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 4

Resolution: metadata mismatch; local_arxiv, observed 2026-05-18T00:25:32.907017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 13fbc2ee-2787-43d6-8c9c-b1a7012d5f33 · inbound

Bgolearn: a Unified Bayesian Optimization Framework for Accelerating Materials Discovery cites this paper.

Bgolearn: a Unified Bayesian Optimization Framework for Accelerating Materials Discovery Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-03T11:21:47.494449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 637d9b4a-caa4-4b08-8a2f-7c7949d6f024 · inbound

Regime-Adaptive Bayesian Optimization via Dirichlet Process Mixtures of Gaussian Processes cites this paper.

Regime-Adaptive Bayesian Optimization via Dirichlet Process Mixtures of Gaussian Processes Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 523

Resolution: unresolved; no resolver link, observed 2026-08-03T07:37:11.822529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b14199f-0944-4aeb-a5de-bc5a86bd3095 · inbound

One-Step Bellman Alignment Enables Provably Efficient Transfer in Online RL cites this paper.

One-Step Bellman Alignment Enables Provably Efficient Transfer in Online RL Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-03T06:51:17.676045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 358b8568-6b06-4b55-b561-021ae282ae5e · inbound

Laser-Enhanced Contact Optimization in Silicon Photovoltaics: Mechanisms, Reliability, and Predictive Process Design cites this paper.

Laser-Enhanced Contact Optimization in Silicon Photovoltaics: Mechanisms, Reliability, and Predictive Process Design Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 138

Resolution: verified exact; local_arxiv, observed 2026-05-19T18:02:42.385950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cdfe4c81-f543-46ed-97b6-d621cc4f1e02 · inbound

The Problem of Dynamic Spatial Sampling and Geofence Surveillance cites this paper.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b05fa01a-6436-477f-83ac-d0ad3d31f6d5 · inbound

Multi-Agent Pathfinding with Non-Unit Integer Edge Costs via Enhanced Conflict-Based Search and Graph Discretization cites this paper.

Multi-Agent Pathfinding with Non-Unit Integer Edge Costs via Enhanced Conflict-Based Search and Graph Discretization Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-10T23:30:52.409757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2cf81d02-193e-4543-9593-be1e59657fca · inbound

When Do We Need LLMs? A Diagnostic for Language-Driven Bandits cites this paper.

When Do We Need LLMs? A Diagnostic for Language-Driven Bandits Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-11T00:25:51.318553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation aa4bd1f7-4f48-44d9-8a85-cbaa9dbe3e51 · inbound

Optimistic Policy Learning under Pessimistic Adversaries with Regret and Violation Guarantees cites this paper.

Optimistic Policy Learning under Pessimistic Adversaries with Regret and Violation Guarantees Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-10T13:40:27.179682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d4fcc011-a4e6-4130-8b08-d55ab083819d · inbound

Spectral bandits cites this paper.

Spectral bandits Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 54

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T00:36:15.606270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a561c013-74c6-4a3c-a994-f4b64aab4b04 · inbound

Decoupled PFNs: Identifiable Epistemic-Aleatoric Decomposition via Structured Synthetic Priors cites this paper.

Decoupled PFNs: Identifiable Epistemic-Aleatoric Decomposition via Structured Synthetic Priors Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T21:36:15.616358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8ffc1520-8824-40c8-a634-b5769a0505ba · inbound

Learning myopic mixed-integer nonlinear model predictive control from expert demonstrations cites this paper.

Learning myopic mixed-integer nonlinear model predictive control from expert demonstrations Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 51

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T03:50:54.679634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cbf94aa6-63c9-46b5-ac5b-a067ed4dc26c · inbound

ADKO: Agentic Decentralized Knowledge Optimization cites this paper.

ADKO: Agentic Decentralized Knowledge Optimization Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:40:53.364738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 24577355-d4e4-4187-aa5f-46cb216afdcd · inbound

Bayesian Optimization of Crossbar-Based Compute-In-Memory System Design for Efficient DNN Inference cites this paper.

Bayesian Optimization of Crossbar-Based Compute-In-Memory System Design for Efficient DNN Inference Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:21:23.611077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b8e9e44a-65da-473e-b4fb-e57726097ca0 · inbound

Many Needles in a Haystack: Active Hit Discovery for Perturbation Experiments cites this paper.

Many Needles in a Haystack: Active Hit Discovery for Perturbation Experiments Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 25

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T07:06:35.915082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 31ea5097-443e-455f-8e7b-4e00a7ce6213 · inbound

FORGE: Fragment-Oriented Ranking and Generation for Context-Aware Molecular Optimization cites this paper.

FORGE: Fragment-Oriented Ranking and Generation for Context-Aware Molecular Optimization Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 42

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T05:26:22.121653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 53186c8b-aeb3-46da-a819-919bfafe92f9 · inbound

Active Learning for Gaussian Process Regression Under Self-Induced Boltzmann Weights cites this paper.

Active Learning for Gaussian Process Regression Under Self-Induced Boltzmann Weights Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 19

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T06:21:25.472587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f696f694-45a9-41c7-b940-ec4b59dd0764 · inbound

Unleashing LLMs in Bayesian Optimization: Preference-Guided Framework for Scientific Discovery cites this paper.

Unleashing LLMs in Bayesian Optimization: Preference-Guided Framework for Scientific Discovery Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 2

Resolution: metadata mismatch; local_arxiv, observed 2026-05-20T10:03:25.452243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 432db537-610e-4675-a016-846d2b3a380f · inbound

Nonparametric Learning and Earning with One-Point Feedback under Nonstationarity cites this paper.

Nonparametric Learning and Earning with One-Point Feedback under Nonstationarity Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 53

Resolution: metadata mismatch; local_arxiv, observed 2026-05-21T05:09:38.829656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c3c362c8-1dd7-454c-a096-7e0cec8006bb · inbound

Regret-Based $(\epsilon,\delta)$-optimal Stopping Criteria for Bayesian Optimization cites this paper.

Regret-Based $(\epsilon,\delta)$-optimal Stopping Criteria for Bayesian Optimization Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-05-22T07:24:43.165845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ec8c1907-720e-434e-a579-91bbf11bf1fb · inbound

Self-Improvement Imitation with Biologically Guided Search for Protein Design Under Oracle Budgets cites this paper.

Self-Improvement Imitation with Biologically Guided Search for Protein Design Under Oracle Budgets Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-06-29T19:23:53.836531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 04b762f6-3001-4416-9f11-54cea3d4a8bf · inbound

CRAFT: Cost-aware Refinement And Front-aware Tuning of Prompts cites this paper.

CRAFT: Cost-aware Refinement And Front-aware Tuning of Prompts Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 244

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T07:46:46.430076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d37127fc-c5d1-458c-8cba-6f48301b7b6f · inbound

Improving Bayesian Optimization via Training-Aware Conditional Diffusion Models cites this paper.

Improving Bayesian Optimization via Training-Aware Conditional Diffusion Models Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-07-02T23:17:29.682610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b7f3798e-b6ba-47da-a2ac-883391bbe280 · inbound

P-K-GCN: Physics-augmented Koopman-enhanced Graph Convolutional Network for Deep Spatiotemporal Super-resolution cites this paper.

P-K-GCN: Physics-augmented Koopman-enhanced Graph Convolutional Network for Deep Spatiotemporal Super-resolution Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 175

Resolution: metadata mismatch; local_arxiv, observed 2026-07-04T00:59:19.205353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 296688df-38f0-44e2-bebb-1b9d57979dcb · inbound

Asymptotically Optimal Learning for Parametric Prophet Inequalities cites this paper.

Asymptotically Optimal Learning for Parametric Prophet Inequalities Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 35

Resolution: metadata mismatch; local_arxiv, observed 2026-07-04T13:49:52.026179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ec32c8cb-4b58-4748-b709-5f65ab4012d2 · inbound

STEMGym: Benchmarking Sequential Decision-Making under Dose Budgets in Autonomous Electron Microscopy cites this paper.

STEMGym: Benchmarking Sequential Decision-Making under Dose Budgets in Autonomous Electron Microscopy Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-06-30T07:24:21.052481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation de2f0c68-0466-404c-a5c5-aaeaa4fd37e7 · inbound

Balancing Expressivity and Learnability in Quantum Kernel Bandit Optimization cites this paper.

Balancing Expressivity and Learnability in Quantum Kernel Bandit Optimization Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 44

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T15:57:06.453566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4a878a5e-7b6c-4287-9734-21fb739f839b · inbound

How to Guide LLM Generation: Dual-Surrogate Guided Search for Automated Heuristic Design cites this paper.

How to Guide LLM Generation: Dual-Surrogate Guided Search for Automated Heuristic Design Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T03:27:19.229973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87b0bdfd-a987-4d75-9e07-755c3aeb49a8 · inbound

Information-Based Exploration via Random Features for Reinforcement Learning cites this paper.

Information-Based Exploration via Random Features for Reinforcement Learning Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T16:35:00.673870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19056ae3-6e49-4121-b910-8c354961a628 · inbound

ALAS: Additive Learnable Alpha-Stable Kernels for Flexible Bayesian Optimization cites this paper.

ALAS: Additive Learnable Alpha-Stable Kernels for Flexible Bayesian Optimization Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T09:29:36.420479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8e72f0a-b7ef-4112-be84-c09f90f67c88 · inbound

Bayesian Retraction Optimization for Tissue Attachment Mapping in Surgical Dissection cites this paper.

Bayesian Retraction Optimization for Tissue Attachment Mapping in Surgical Dissection Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T13:18:20.554775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfc23e08-9b9b-4d48-bb18-70cfe46ea704 · inbound

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds cites this paper.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-30T21:57:09.733021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.