SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 571–580 of 2226 papers

TitleStatusHype
Push: Concurrent Probabilistic Programming for Bayesian Deep LearningCode0
Bayesian Knowledge-driven Critiquing with Indirect Evidence—0
In-Context Learning through the Bayesian PrismCode0
Entropy-based Training Methods for Scalable Neural Implicit Sampler—0
Latent Optimal Paths by Gumbel Propagation for Variational Bayesian Dynamic ProgrammingCode0
Interval Load Forecasting for Individual Households in the Presence of Electric Vehicle Charging—0
ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive AdvantagesCode0
Robust Bayesian Inference for Berkson and Classical Measurement Error Models—0
On Mixing Rates for Bayesian CART—0
Metropolis-Hastings algorithm in joint-attention naming game: Experimental semiotics study—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1F-SWAAccuracy83.61—Unverified
2F-SWAGAccuracy80.93—Unverified