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Energy Consumption Analysis Details
The spike firing rate is defined as the proportion of non-zero elements in the spike tensor. In Table S1, we present the spike firing rates for all spiking tensors in spike-driven Transformer-8-512. SNNs are theoretically more energy efficient than counterpart ANNs. We employ two types of datasets: static image classification and neuromorphic classification. ImageNet-1K is the most typical static image dataset, which is widely used in the field of image classification.
Decomposable Transformer Point Processes
Despite the flexibility of these methods, their inference is based on the computationally intensive thinning algorithm.
Meta-Learning with Neural Bandit Scheduler Y unzhe Qi
However, this assumption can possibly fail in real-world scenarios.
Appendix for Bayesian Active Causal Discovery with Multi-Fidelity Experiments Anonymous Author(s) Affiliation Address email
Then, we intend to calculate the constraint part. The algorithm for Licence method for single-target interventiion scenario is shown in Algorithm 1. The details of experimental baselines are demonstrated as follows. AIT [11] is an active learning method that utilize f-score to select intervention queries. REAL fidelity means the model always choose the highest fidelity to conduct experiments.
Bayesian Active Causal Discovery with Multi-Fidelity Experiments
For example, to study the causal relations between the drugs and diseases, one can conduct clinical tests via selectively administering the medicines to the patients.
