Protein design and engineering has become a crucial component of pharmaceutical research and development, finding application in a wide variety of diagnostic and industrial settings.

I liked that it was a puzzle.

In this section we provide proofs of theoretical statements in the paper. These authors contributed equally to this work. Here, the columns are described as follows: "Dec." "Entropy" indicates whether the conditional-entropy loss is being used. "Pseudo-labels" indicates whether pseudo-labels are being used.

In this appendix, we start with describing the experimental setup details (Sec. Each sampled video from 30K has on average around 100 clips. To investigate whether the additional MLP distillation head (Sec.3.3 in the main paper) affects the As we see in Table 1, for both NST and CRD, the performance drops on all downstream tasks when distillation heads are removed. Table 1: Ablation results of additional distillation heads for student language models.SST -2 QNLI QQP MNLI BERT In Table 2, we compare the accuracy of text-only pretraining, image-based KD and video-based KD on PIQA. KD further improves the results.

Multi-fidelity modeling and learning is important in physical simulation related applications.

KITTI 2012 contains 194 training image pairs and 195 test image pairs. We use a maximum disparity level of 192 in this dataset. Most of the stereo pairs are indoor scenes with handcrafted layouts. This dataset contains many thin objects and large disparity ranges. We provide more qualitative results on the SceneFlow, KITTI 2012, KITTI 2015 and Middlebury datasets in Figure 1 2 3 4, respectively.

The code is available at LEAStereo.