Unverified50% confidenceBenchmarkExact time
Monte Carlo Dropout entropy, as an alternative metric, successfully captured distribution shift in all eight test events.
1
Sources
50%
Confidence
Long-term
Relevance
10/8/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedDue to non-determinism, the same Eval should be run 6 to 10 times to observe the distribution range of accuracy and calculate standard deviation and error.65% similarUnverifiedWhen using a constant entropy reward, the network got stuck in a suboptimal solution in 5 out of 6 runs; after annealing the entropy coefficient from 0.1 to 0.005 over the first 10,000 attempts, the number of times it got stuck dropped to only 1 out of 6.64% similarUnverifiedAssuming the data follows a Bernoulli or multinomial distribution, maximizing the likelihood is equivalent to minimizing the cross-entropy loss function.64% similarUnverified实验采用8:2比例划分数据，20%作为内部测试集，训练集内部使用5折交叉验证，并移除重复记录以避免数据泄漏63% similarUnverified当不动动作占据80%以上帧时，模型通过最小化交叉熵损失可在不学习有意义特征的情况下达到80%准确率，这称为多数类捷径63% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/986744API
curl https://kongchang.com/api/v1/knowledge/claims/986744MCP
get_claim(id=986744)