2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2024★ 2 cited
Training Bayesian Neural Networks with Sparse Subspace Variational Inference
Junbo Li, Zichen Miao, Qiang Qiu +1
Bayesian neural networks (BNNs) offer uncertainty quantification but come with the downside of substantially increased training and inference costs. Sparse BNNs have been investiga…
cs.LG2023
Long-tailed Classification from a Bayesian-decision-theory Perspective
Bolian Li, Ruqi Zhang
Long-tailed classification poses a challenge due to its heavy imbalance in class probabilities and tail-sensitivity risks with asymmetric misprediction costs. Recent attempts have…
cs.LG2023
Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation
Yue Xiang, Dongyao Zhu, Bowen Lei +2
Gradients have been exploited in proposal distributions to accelerate the convergence of Markov chain Monte Carlo algorithms on discrete distributions. However, these methods requi…