RoQNN: Noise-Aware Training for Robust Quantum Neural Networks
Github: https://github.com/mit-han-lab/pytorch-quantum
Paper: https://arxiv.org/abs/2110.11331v1
Dataset: https://paperswithcode.com/dataset/mnist
@ArtificialIntelligencedl
Github: https://github.com/mit-han-lab/pytorch-quantum
Paper: https://arxiv.org/abs/2110.11331v1
Dataset: https://paperswithcode.com/dataset/mnist
@ArtificialIntelligencedl
Generalized Out-of-Distribution Detection: A Survey
Github: https://github.com/jingkang50/oodsurvey
Paper: https://arxiv.org/abs/2110.11334v1
@ArtificialIntelligencedl
Github: https://github.com/jingkang50/oodsurvey
Paper: https://arxiv.org/abs/2110.11334v1
@ArtificialIntelligencedl
Multi-label Classification with Partial Annotations using Class-aware Selective Loss
Github: https://github.com/alibaba-miil/partiallabelingcsl
Paper: https://arxiv.org/abs/2110.10955v1
Dataset: https://arxiv.org/abs/2110.10955v1
@ArtificialIntelligencedl
Github: https://github.com/alibaba-miil/partiallabelingcsl
Paper: https://arxiv.org/abs/2110.10955v1
Dataset: https://arxiv.org/abs/2110.10955v1
@ArtificialIntelligencedl
Subject Adaptive EEG-based Visual Recognition
Github: https://github.com/DeepBCI/Deep-BCI
Paper: https://arxiv.org/abs/2110.13470v1
Dataset: https://paperswithcode.com/dataset/imagenet
@ArtificialIntelligencedl
Github: https://github.com/DeepBCI/Deep-BCI
Paper: https://arxiv.org/abs/2110.13470v1
Dataset: https://paperswithcode.com/dataset/imagenet
@ArtificialIntelligencedl
Subject Adaptive EEG-based Visual Recognition
Github: https://github.com/junsu-kim97/higl
Paper: https://arxiv.org/abs/2110.13625v2
Dataset: https://paperswithcode.com/dataset/mujoco
@ArtificialIntelligencedl
Github: https://github.com/junsu-kim97/higl
Paper: https://arxiv.org/abs/2110.13625v2
Dataset: https://paperswithcode.com/dataset/mujoco
@ArtificialIntelligencedl
Subject Adaptive EEG-based Visual Recognition
Github: https://github.com/rll-research/url_benchmark
Paper: https://arxiv.org/abs/2110.15191v1
Dataset: https://paperswithcode.com/dataset/openai-gym
@ArtificialIntelligencedl
Github: https://github.com/rll-research/url_benchmark
Paper: https://arxiv.org/abs/2110.15191v1
Dataset: https://paperswithcode.com/dataset/openai-gym
@ArtificialIntelligencedl
🔊 Torchaudio: an audio library for PyTorch
Github: https://github.com/pytorch/audio
Paper: https://arxiv.org/abs/2110.15018v1
Dataset: https://paperswithcode.com/dataset/ljspeech
@ArtificialIntelligencedl
Github: https://github.com/pytorch/audio
Paper: https://arxiv.org/abs/2110.15018v1
Dataset: https://paperswithcode.com/dataset/ljspeech
@ArtificialIntelligencedl
⛓ Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training
Github: https://github.com/hpcaitech/colossalai
Paper: https://arxiv.org/abs/2110.14883v1
@ArtificialIntelligencedl
Github: https://github.com/hpcaitech/colossalai
Paper: https://arxiv.org/abs/2110.14883v1
@ArtificialIntelligencedl
Exploring the Semi-supervised Video Object Segmentation Problem from a Cyclic Perspective
Github: https://github.com/lyxok1/STM-Training
Paper: https://arxiv.org/abs/2111.01323v1
Dataset: https://paperswithcode.com/dataset/coco
@ArtificialIntelligencedl
Github: https://github.com/lyxok1/STM-Training
Paper: https://arxiv.org/abs/2111.01323v1
Dataset: https://paperswithcode.com/dataset/coco
@ArtificialIntelligencedl
🥇 Towards Sparse Federated Analytics: Location Heatmaps under Distributed Differential Privacy with Secure Aggregation
Github: https://github.com/google-research/federated
Paper: https://arxiv.org/abs/2111.02356v1
@ArtificialIntelligencedl
Github: https://github.com/google-research/federated
Paper: https://arxiv.org/abs/2111.02356v1
@ArtificialIntelligencedl
RLDS: an Ecosystem to Generate, Share and Use Datasets in Reinforcement Learning
Github: https://github.com/google-research/rlds
Paper: https://arxiv.org/abs/2111.02767v1
Dataset: https://paperswithcode.com/dataset/d4rl
@ArtificialIntelligencedl
Github: https://github.com/google-research/rlds
Paper: https://arxiv.org/abs/2111.02767v1
Dataset: https://paperswithcode.com/dataset/d4rl
@ArtificialIntelligencedl
Deep Neural Networks to Detect Weeds from Crops in Agricultural Environments in Real-Time: A Review
Github: https://github.com/Ildaron/Laser_control
Paper: https://www.mdpi.com/2072-4292/13/21/4486
@ArtificialIntelligencedl
Github: https://github.com/Ildaron/Laser_control
Paper: https://www.mdpi.com/2072-4292/13/21/4486
@ArtificialIntelligencedl
Multiscale Deep Equilibrium Models
Github: https://github.com/locuslab/mdeq
Paper: https://arxiv.org/abs/2111.05177v1
Dataset: https://paperswithcode.com/dataset/cifar-10
@ArtificialIntelligencedl
Github: https://github.com/locuslab/mdeq
Paper: https://arxiv.org/abs/2111.05177v1
Dataset: https://paperswithcode.com/dataset/cifar-10
@ArtificialIntelligencedl
Theoretical and empirical analysis of a fast algorithm for extracting polygons from signed distance bounds
Github: https://github.com/nenadmarkus/gridhopping
Paper: https://arxiv.org/abs/2111.05778v1
@ArtificialIntelligencedl
Github: https://github.com/nenadmarkus/gridhopping
Paper: https://arxiv.org/abs/2111.05778v1
@ArtificialIntelligencedl
Self-Supervised Audio-Visual Representation Learning with Relaxed Cross-Modal Temporal Synchronicity
Github:https://github.com/pritamqu/CrissCross
Paper: https://arxiv.org/abs/2111.05329v1
Project: https://pritamqu.github.io/CrissCross/
@ArtificialIntelligencedl
Github:https://github.com/pritamqu/CrissCross
Paper: https://arxiv.org/abs/2111.05329v1
Project: https://pritamqu.github.io/CrissCross/
@ArtificialIntelligencedl
🔹 LUMINOUS: Indoor Scene Generation for Embodied AI Challenges
Github: https://github.com/amazon-research/indoor-scene-generation-eai
Paper: https://arxiv.org/abs/2111.05527v1
Dataset: https://paperswithcode.com/dataset/ai2-thor
@ArtificialIntelligencedl
Github: https://github.com/amazon-research/indoor-scene-generation-eai
Paper: https://arxiv.org/abs/2111.05527v1
Dataset: https://paperswithcode.com/dataset/ai2-thor
@ArtificialIntelligencedl
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A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents
Github: https://github.com/extreme-classification/deepxml
Paper: https://arxiv.org/abs/2111.06685v1
Dataset: https://paperswithcode.com/dataset/extreme-classification
@ArtificialIntelligencedl
Github: https://github.com/extreme-classification/deepxml
Paper: https://arxiv.org/abs/2111.06685v1
Dataset: https://paperswithcode.com/dataset/extreme-classification
@ArtificialIntelligencedl
https://news.1rj.ru/str/Machinelearningtest - machine learning tests
Fast and Credible Likelihood-Free Cosmology with Truncated Marginal Neural Ratio Estimation
Github: https://github.com/undark-lab/swyft
Paper: https://arxiv.org/abs/2111.08030v1
Docs: https://swyft.readthedocs.io/en/latest/
@ArtificialIntelligencedl
Github: https://github.com/undark-lab/swyft
Paper: https://arxiv.org/abs/2111.08030v1
Docs: https://swyft.readthedocs.io/en/latest/
@ArtificialIntelligencedl
GitHub
GitHub - undark-lab/swyft: A system for scientific simulation-based inference at scale.
A system for scientific simulation-based inference at scale. - undark-lab/swyft
🔥1
ClipCap: CLIP Prefix for Image Captioning
Github: https://github.com/rmokady/clip_prefix_caption
Paper: https://arxiv.org/abs/2111.09734v1
Dataset: https://paperswithcode.com/dataset/conceptual-captions
@ArtificialIntelligencedl
Github: https://github.com/rmokady/clip_prefix_caption
Paper: https://arxiv.org/abs/2111.09734v1
Dataset: https://paperswithcode.com/dataset/conceptual-captions
@ArtificialIntelligencedl