TRACE creates valid conformal prediction sets for complex generative models by scoring outputs via averaged denoising or velocity errors along stochastic transport paths instead of likelihoods.
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10 Pith papers cite this work. Polarity classification is still indexing.
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HAPS constructs shorter conformal prediction sets for censored time-to-event outcomes by using time-varying covariate histories and IPCW, achieving approximate coverage among survivors with up to 75% shorter intervals in simulations.
Super-level-set regression directly optimizes conditional level-set boundaries via volume minimization to achieve minimum-volume prediction regions with conditional coverage.
Trimming helps conformal prediction under contamination precisely when the anomaly score separates retention probabilities without biasing clean scores, otherwise the retained mixture coefficient prevents substantial decontamination.
A classification-integrated conformal framework for zero-inflated outcomes that guarantees marginal coverage and asymptotic minimal length under exchangeability, independent of the underlying models.
DC-TNN decomposes tensors into low-rank core plus sparse refinement fed to coupled neural channels, yielding non-asymptotic risk bounds and the first distribution-free conformal procedure for selecting among tensor decompositions.
A fair conformal classification method guarantees conditional coverage on adaptively identified subgroups defined via learned representations.
CONTRA generates sharp multi-dimensional conformal prediction regions by defining nonconformity scores as distances from the center in the latent space of a normalizing flow.
CPR improves empirical coverage rate by 34% and reduces average prediction set size by 40% in KGQA benchmarks via query-level path calibration and RCVNet for discriminative nonconformity scores.
SA-BCP achieves optimal spatio-temporal decoupling in Bayesian conformal prediction by gating temporal inertia with spatial kernel-density evidence, governed by a minimax bias-variance threshold K, and outperforms ACI and Bayesian CP baselines on financial datasets.
citing papers explorer
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TRACE: Transport Alignment Conformal Prediction via Diffusion and Flow Matching Models
TRACE creates valid conformal prediction sets for complex generative models by scoring outputs via averaged denoising or velocity errors along stochastic transport paths instead of likelihoods.
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History-Aware Conformal Prediction Sets for Censored Time-to-Event Outcomes
HAPS constructs shorter conformal prediction sets for censored time-to-event outcomes by using time-varying covariate histories and IPCW, achieving approximate coverage among survivors with up to 75% shorter intervals in simulations.
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Super-Level-Set Regression: Conditional Quantiles via Volume Minimization
Super-level-set regression directly optimizes conditional level-set boundaries via volume minimization to achieve minimum-volume prediction regions with conditional coverage.
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When Does Trimming Help Conformal Prediction? A Retained-Law Diagnostic under Calibration Contamination
Trimming helps conformal prediction under contamination precisely when the anomaly score separates retention probabilities without biasing clean scores, otherwise the retained mixture coefficient prevents substantial decontamination.
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Classification-Powered Conformal Inference for Zero-inflated Outcomes
A classification-integrated conformal framework for zero-inflated outcomes that guarantees marginal coverage and asymptotic minimal length under exchangeability, independent of the underlying models.
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Dual-Channel Tensor Neural Networks: Finite-Sample Theory and Conformal Structure Selection
DC-TNN decomposes tensors into low-rank core plus sparse refinement fed to coupled neural channels, yielding non-asymptotic risk bounds and the first distribution-free conformal procedure for selecting among tensor decompositions.
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Fair Conformal Classification via Learning Representation-Based Groups
A fair conformal classification method guarantees conditional coverage on adaptively identified subgroups defined via learned representations.
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CONTRA: Conformal Prediction Region via Normalizing Flow Transformation
CONTRA generates sharp multi-dimensional conformal prediction regions by defining nonconformity scores as distances from the center in the latent space of a normalizing flow.
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Conformal Path Reasoning: Trustworthy Knowledge Graph Question Answering via Path-Level Calibration
CPR improves empirical coverage rate by 34% and reduces average prediction set size by 40% in KGQA benchmarks via query-level path calibration and RCVNet for discriminative nonconformity scores.
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Optimal Spatio-Temporal Decoupling for Bayesian Conformal Prediction
SA-BCP achieves optimal spatio-temporal decoupling in Bayesian conformal prediction by gating temporal inertia with spatial kernel-density evidence, governed by a minimax bias-variance threshold K, and outperforms ACI and Bayesian CP baselines on financial datasets.