Robust Reference-based Super-Resolution via C2-Matching
Github: https://github.com/yumingj/C2-Matching
Paper: https://arxiv.org/abs/2106.01863v1
👉 @bigdata_1
Github: https://github.com/yumingj/C2-Matching
Paper: https://arxiv.org/abs/2106.01863v1
👉 @bigdata_1
👍2
QRec is a Python framework for recommender systems
Github: https://github.com/Coder-Yu/QRec
Paper: https://arxiv.org/abs/2106.03569v1
👉 @bigdata_1
Github: https://github.com/Coder-Yu/QRec
Paper: https://arxiv.org/abs/2106.03569v1
👉 @bigdata_1
👍1
abess: Fast Best-Subset Selection in Python and R
Github: https://github.com/abess-team/abess
Docs: https://abess.readthedocs.io/en/latest/Tutorial/index.html
Paper: https://arxiv.org/abs/2110.09697v1
👉 @bigdata_1
Github: https://github.com/abess-team/abess
Docs: https://abess.readthedocs.io/en/latest/Tutorial/index.html
Paper: https://arxiv.org/abs/2110.09697v1
👉 @bigdata_1
Efficient Iterative Amortized Inference for Learning Symmetric and Disentangled Multi-object Representations
Github: https://github.com/pemami4911/EfficientMORL
Paper: https://arxiv.org/abs/2106.03630v1
👉 @bigdata_1
Github: https://github.com/pemami4911/EfficientMORL
Paper: https://arxiv.org/abs/2106.03630v1
👉 @bigdata_1
HRFormer: High-Resolution Transformer for Dense Prediction, NeurIPS 2021
Github: https://github.com/HRNet/HRFormer
Paper: https://arxiv.org/abs/2110.09408v1
Dataset: https://paperswithcode.com/dataset/coco
👉 @bigdata_1
Github: https://github.com/HRNet/HRFormer
Paper: https://arxiv.org/abs/2110.09408v1
Dataset: https://paperswithcode.com/dataset/coco
👉 @bigdata_1
Pretraining Representations for Data-Efficient Reinforcement Learning
Github: https://github.com/mila-iqia/spr
Paper: https://arxiv.org/abs/2106.04799v1
👉 @bigdata_1
Github: https://github.com/mila-iqia/spr
Paper: https://arxiv.org/abs/2106.04799v1
👉 @bigdata_1
SecureBoost+ : A High Performance Gradient Boosting Tree Framework for Large Scale Vertical Federated Learning
Github: https://github.com/FederatedAI/FATE
Paper: https://arxiv.org/abs/2110.10927v1
👉 @bigdata_1
Github: https://github.com/FederatedAI/FATE
Paper: https://arxiv.org/abs/2110.10927v1
👉 @bigdata_1
Score Matching Model for Unbounded Data Score
Github: https://github.com/Kim-Dongjun/UNCSN
Paper: https://arxiv.org/abs/2106.05527v1
👉 @bigdata_1
Github: https://github.com/Kim-Dongjun/UNCSN
Paper: https://arxiv.org/abs/2106.05527v1
👉 @bigdata_1
👍1
Bi-directional Image and Text Generation
Github: https://github.com/researchmm/generate-it
Paper: https://arxiv.org/abs/2110.09753v1
Dataset: https://paperswithcode.com/dataset/coco
👉 @bigdata_1
Github: https://github.com/researchmm/generate-it
Paper: https://arxiv.org/abs/2110.09753v1
Dataset: https://paperswithcode.com/dataset/coco
👉 @bigdata_1
GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings
Github: https://github.com/rusty1s/pyg_autoscale
Paper: https://arxiv.org/abs/2106.05609v1
👉 @bigdata_1
Github: https://github.com/rusty1s/pyg_autoscale
Paper: https://arxiv.org/abs/2106.05609v1
👉 @bigdata_1
😁1
NAS-FCOS: Fast Neural Architecture Search for Object Detection
Github: https://github.com/Lausannen/NAS-FCOS
Paper: https://arxiv.org/abs/2110.12423v1
👉 @bigdata_1
Github: https://github.com/Lausannen/NAS-FCOS
Paper: https://arxiv.org/abs/2110.12423v1
👉 @bigdata_1
Pivotal Tuning for Latent-based Editing of Real Images
Github: https://github.com/Talegqz/unsupervised_co_part_segmentation
Paper: https://arxiv.org/abs/2106.05897v1
👉 @bigdata_1
Github: https://github.com/Talegqz/unsupervised_co_part_segmentation
Paper: https://arxiv.org/abs/2106.05897v1
👉 @bigdata_1
👍1
Revisiting randomized choices in isolation forests
Github: https://github.com/david-cortes/isotree
Paper: https://arxiv.org/abs/2110.13402v1
👉 @bigdata_1
Github: https://github.com/david-cortes/isotree
Paper: https://arxiv.org/abs/2110.13402v1
👉 @bigdata_1
A Deep Variational Approach to Clustering Survival Data
Github: https://github.com/i6092467/vadesc
Paper: https://arxiv.org/abs/2106.05763v1
👉 @bigdata_1
Github: https://github.com/i6092467/vadesc
Paper: https://arxiv.org/abs/2106.05763v1
👉 @bigdata_1
👍1
GoEmotions: A Dataset for Fine-Grained Emotion Classification
Github: https://github.com/google-research/google-research/tree/master/goemotions
Google AI: https://ai.googleblog.com/2021/10/goemotions-dataset-for-fine-grained.html
👉 @bigdata_1
Github: https://github.com/google-research/google-research/tree/master/goemotions
Google AI: https://ai.googleblog.com/2021/10/goemotions-dataset-for-fine-grained.html
👉 @bigdata_1
Part-aware Panoptic Segmentation
Github: https://github.com/pmeletis/panoptic_parts
Paper: https://arxiv.org/abs/2106.06351v1
Docs: https://panoptic-parts.readthedocs.io/en/stable
👉 @bigdata_1
Github: https://github.com/pmeletis/panoptic_parts
Paper: https://arxiv.org/abs/2106.06351v1
Docs: https://panoptic-parts.readthedocs.io/en/stable
👉 @bigdata_1
OneFlow is a performance-centered and open-source deep learning framework.
Github: https://github.com/Oneflow-Inc/oneflow
Paper: https://arxiv.org/abs/2110.15032v2
👉 @bigdata_1
Github: https://github.com/Oneflow-Inc/oneflow
Paper: https://arxiv.org/abs/2110.15032v2
👉 @bigdata_1
👍1
Optimal transport in multilayer networks
Github: https://github.com/cdebacco/MultiOT
Paper: https://arxiv.org/abs/2106.07202v1
👉 @bigdata_1
Github: https://github.com/cdebacco/MultiOT
Paper: https://arxiv.org/abs/2106.07202v1
👉 @bigdata_1
👍1
StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
Github: https://github.com/POSTECH-CVLab/PyTorch-StudioGAN
Paper: https://arxiv.org/abs/2111.01118v1
Dataset: https://paperswithcode.com/dataset/cifar-10
👉 @bigdata_1
Github: https://github.com/POSTECH-CVLab/PyTorch-StudioGAN
Paper: https://arxiv.org/abs/2111.01118v1
Dataset: https://paperswithcode.com/dataset/cifar-10
👉 @bigdata_1
Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages
Github: https://github.com/cf020031308/LinkDist
Paper: https://arxiv.org/abs/2106.08541v1
👉 @bigdata_1
Github: https://github.com/cf020031308/LinkDist
Paper: https://arxiv.org/abs/2106.08541v1
👉 @bigdata_1