OntoMerger: An Ontology Integration Library for Deduplicating and Connecting Knowledge Graph Nodes
OntoMerger is an ontology alignment library for deduplicating knowledge graph nodes
Github: https://github.com/astrazeneca/onto_merger
Paper: https://arxiv.org/abs/2206.02238v1
Documentation: https://ontomerger.readthedocs.io/
@ArtificialIntelligencedl
OntoMerger is an ontology alignment library for deduplicating knowledge graph nodes
Github: https://github.com/astrazeneca/onto_merger
Paper: https://arxiv.org/abs/2206.02238v1
Documentation: https://ontomerger.readthedocs.io/
@ArtificialIntelligencedl
π6
Tutel: Adaptive Mixture-of-Experts at Scale
Tutel, a highly scalable stack design and implementation for MoE with dynamically adaptive parallelism and pipelining.
Github: https://github.com/microsoft/tutel
Examples: https://github.com/microsoft/tutel/blob/main/tutel/examples
Paper: https://paperswithcode.com/dataset/coco
Documentation: https://ontomerger.readthedocs.io/
@ArtificialIntelligencedl
Tutel, a highly scalable stack design and implementation for MoE with dynamically adaptive parallelism and pipelining.
Github: https://github.com/microsoft/tutel
Examples: https://github.com/microsoft/tutel/blob/main/tutel/examples
Paper: https://paperswithcode.com/dataset/coco
Documentation: https://ontomerger.readthedocs.io/
@ArtificialIntelligencedl
π6
π Sparse Fusion Mixture-of-Experts are Domain Generalizable Learners
Sparse Fusion Mixture-of-Experts (SF-MoE), which incorporates sparsity and fusion mechanisms into the MoE framework to keep the model both sparse and predictive.
Github: https://github.com/luodian/sf-moe-dg
Paper: https://arxiv.org/abs/2206.04046v1
Documentation: https://paperswithcode.com/dataset/domainnet
@ArtificialIntelligencedl
Sparse Fusion Mixture-of-Experts (SF-MoE), which incorporates sparsity and fusion mechanisms into the MoE framework to keep the model both sparse and predictive.
Github: https://github.com/luodian/sf-moe-dg
Paper: https://arxiv.org/abs/2206.04046v1
Documentation: https://paperswithcode.com/dataset/domainnet
@ArtificialIntelligencedl
π4
πΉ PointNeXt & OpenPoints Library
improved training and model scaling strategies to boost PointNet++ to the state-of-the-art level.
Github: https://github.com/guochengqian/pointnext
Paper: https://paperswithcode.com/dataset/shapenet
@ArtificialIntelligencedl
improved training and model scaling strategies to boost PointNet++ to the state-of-the-art level.
Github: https://github.com/guochengqian/pointnext
Paper: https://paperswithcode.com/dataset/shapenet
@ArtificialIntelligencedl
π5
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Github: https://github.com/google/BIG-bench
Paper: https://arxiv.org/abs/2206.04615v1
Dataset: https://paperswithcode.com/dataset/glue
@ArtificialIntelligencedl
Github: https://github.com/google/BIG-bench
Paper: https://arxiv.org/abs/2206.04615v1
Dataset: https://paperswithcode.com/dataset/glue
@ArtificialIntelligencedl
β€8
Revisiting End-to-End Speech-to-Text Translation From Scratch
Github: https://github.com/bzhangGo/zero
Paper: https://arxiv.org/abs/2206.04571v1
Dataset: https://paperswithcode.com/dataset/must-c
@ArtificialIntelligencedl
Github: https://github.com/bzhangGo/zero
Paper: https://arxiv.org/abs/2206.04571v1
Dataset: https://paperswithcode.com/dataset/must-c
@ArtificialIntelligencedl
π6
π SoundSpaces 2.0: A Simulation Platform for Visual-Acoustic Learning
We introduce SoundSpaces 2.0, a platform for on-the-fly geometry-based audio rendering for 3D environments.
Github: https://github.com/facebookresearch/sound-spaces
Paper: https://arxiv.org/abs/2206.08312v1
Dataset: https://paperswithcode.com/dataset/librispeech
We introduce SoundSpaces 2.0, a platform for on-the-fly geometry-based audio rendering for 3D environments.
Github: https://github.com/facebookresearch/sound-spaces
Paper: https://arxiv.org/abs/2206.08312v1
Dataset: https://paperswithcode.com/dataset/librispeech
Meta Optimal Transport
Github: https://github.com/facebookresearch/meta-ot
Paper: https://arxiv.org/abs/2206.05262v1
@ArtificialIntelligencedl
Github: https://github.com/facebookresearch/meta-ot
Paper: https://arxiv.org/abs/2206.05262v1
@ArtificialIntelligencedl
π2
π¦ Featurized Query R-CNN
Featurized object queries predicted by a query generation network in the well-established Faster R-CNN framework and develop a Featurized Query R-CN
Github: https://github.com/hustvl/featurized-queryrcnn
Paper: https://arxiv.org/abs/2206.06258v1
Dataset: https://paperswithcode.com/dataset/crowdhuman
@ArtificialIntelligencedl
Featurized object queries predicted by a query generation network in the well-established Faster R-CNN framework and develop a Featurized Query R-CN
Github: https://github.com/hustvl/featurized-queryrcnn
Paper: https://arxiv.org/abs/2206.06258v1
Dataset: https://paperswithcode.com/dataset/crowdhuman
@ArtificialIntelligencedl
π4
UniSRec
The proposed approach utilizes the associated description text of items to learn transferable representations across different recommendation scenarios.
Github: https://github.com/rucaibox/unisrec
Paper: https://arxiv.org/abs/2206.05941v1
Google Drive: https://drive.google.com/drive/folders/1Uik0fMk4oquV_bS9lXTZuExAYbIDkEMW?usp=sharing
@ArtificialIntelligencedl
The proposed approach utilizes the associated description text of items to learn transferable representations across different recommendation scenarios.
Github: https://github.com/rucaibox/unisrec
Paper: https://arxiv.org/abs/2206.05941v1
Google Drive: https://drive.google.com/drive/folders/1Uik0fMk4oquV_bS9lXTZuExAYbIDkEMW?usp=sharing
@ArtificialIntelligencedl
π₯3
π LET-3D-AP: Longitudinal Error Tolerant 3D Average Precision for Camera-Only 3D Detection
Waymo Open Dataset publicly to aid the research community in making advancements in machine perception and autonomous driving technology.
Github: https://github.com/waymo-research/waymo-open-dataset
Paper: https://arxiv.org/abs/2206.07705v1
Dataset: https://paperswithcode.com/dataset/waymo-open-datasetg
@ArtificialIntelligencedl
Waymo Open Dataset publicly to aid the research community in making advancements in machine perception and autonomous driving technology.
Github: https://github.com/waymo-research/waymo-open-dataset
Paper: https://arxiv.org/abs/2206.07705v1
Dataset: https://paperswithcode.com/dataset/waymo-open-datasetg
@ArtificialIntelligencedl
π2
Forwarded from Machinelearning
π StrengthNet
Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis"
Github: https://github.com/ttslr/strengthnet
Paper: https://arxiv.org/abs/2110.03156
MOSNet: https://github.com/lochenchou/MOSNet
@ai_machinelearning_big_data
Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis"
Github: https://github.com/ttslr/strengthnet
Paper: https://arxiv.org/abs/2110.03156
MOSNet: https://github.com/lochenchou/MOSNet
@ai_machinelearning_big_data
π5
DeepFormableTag: End-to-end Generation and Recognition of Deformable Fiducial Markers
Github: https://github.com/KAIST-VCLAB/DeepFormableTag
Project: https://vclab.kaist.ac.kr/siggraph2021/index.html
Paper: https://vclab.kaist.ac.kr/siggraph2021/DeepFormableTag-main-screen.pdf
Dataset: https://drive.google.com/drive/folders/1picphIb6Hbj6pM3Wu_Vxu53wzKBV0jdV
@ArtificialIntelligencedl
Github: https://github.com/KAIST-VCLAB/DeepFormableTag
Project: https://vclab.kaist.ac.kr/siggraph2021/index.html
Paper: https://vclab.kaist.ac.kr/siggraph2021/DeepFormableTag-main-screen.pdf
Dataset: https://drive.google.com/drive/folders/1picphIb6Hbj6pM3Wu_Vxu53wzKBV0jdV
@ArtificialIntelligencedl
π5
π Spatially-Adapive Multilayer (SAM) Inversion
Proposed method automatically selects the latent space tailored for each region to balance the reconstruction quality and editability (3rd row).
Github: https://github.com/adobe-research/sam_inversion
Project: https://www.cs.cmu.edu/~SAMInversion/
Paper: https://arxiv.org/abs/2206.08357
@ArtificialIntelligencedl
Proposed method automatically selects the latent space tailored for each region to balance the reconstruction quality and editability (3rd row).
Github: https://github.com/adobe-research/sam_inversion
Project: https://www.cs.cmu.edu/~SAMInversion/
Paper: https://arxiv.org/abs/2206.08357
@ArtificialIntelligencedl
π5
Automatic Prosody Annotation with Pre-Trained Text-Speech Model
Github: https://github.com/daisyqk/automatic-prosody-annotation
Project: https://daisyqk.github.io/Automatic-Prosody-Annotation_w/
Paper: https://arxiv.org/abs/2206.07956v1
@ArtificialIntelligencedl
Github: https://github.com/daisyqk/automatic-prosody-annotation
Project: https://daisyqk.github.io/Automatic-Prosody-Annotation_w/
Paper: https://arxiv.org/abs/2206.07956v1
@ArtificialIntelligencedl
π₯6π2
π¦Ύ Bi-DexHands: Bimanual Dexterous Manipulation via Reinforcement Learning
Bi-DexHands provides a collection of bimanual dexterous manipulations tasks and reinforcement learning algorithms.
Github: https://github.com/pku-marl/dexteroushands
Isaac Gym: https://developer.nvidia.com/isaac-gym
Paper: hhttps://arxiv.org/abs/2206.08686
@ArtificialIntelligencedl
Bi-DexHands provides a collection of bimanual dexterous manipulations tasks and reinforcement learning algorithms.
Github: https://github.com/pku-marl/dexteroushands
Isaac Gym: https://developer.nvidia.com/isaac-gym
Paper: hhttps://arxiv.org/abs/2206.08686
@ArtificialIntelligencedl
π6
πΉ SENSORIUM 2022 Competition
The Sensorium competition on predicting large-scale mouse primary visual cortex activity
Github: https://github.com/sinzlab/sensorium
Website: https://sensorium2022.net/
Paper: https://arxiv.org/abs/2206.08666v1
@ArtificialIntelligencedl
The Sensorium competition on predicting large-scale mouse primary visual cortex activity
Github: https://github.com/sinzlab/sensorium
Website: https://sensorium2022.net/
Paper: https://arxiv.org/abs/2206.08666v1
@ArtificialIntelligencedl
π5
π Object Structural Points Representation for Graph-based Semantic Monocular Localization and Mapping
Github:https://github.com/airlab-polimi/c-slam
Tutorial: https://ros.org/wiki/catkin/Tutorials/create_a_workspace
Paper: https://arxiv.org/abs/2206.10263v1
@ArtificialIntelligencedl
Github:https://github.com/airlab-polimi/c-slam
Tutorial: https://ros.org/wiki/catkin/Tutorials/create_a_workspace
Paper: https://arxiv.org/abs/2206.10263v1
@ArtificialIntelligencedl
π5
π§ Identifying and Combating Bias in Segmentation Networks by leveraging multiple resolutions
Github: https://github.com/Deep-MI/FastSurfer
Colab: https://colab.research.google.com/github/Deep-MI/FastSurfer/blob/master/Tutorial/Tutorial_FastSurferCNN_QuickSeg.ipynb
Paper: https://arxiv.org/abs/2206.14919v1
Github: https://github.com/Deep-MI/FastSurfer
Colab: https://colab.research.google.com/github/Deep-MI/FastSurfer/blob/master/Tutorial/Tutorial_FastSurferCNN_QuickSeg.ipynb
Paper: https://arxiv.org/abs/2206.14919v1
π© Object Structural Points Representation for Graph-based Semantic Monocular Localization and Mapping
PyGOD is a Python library for graph outlier detection (anomaly detection).
Github: https://github.com/pygod-team/pygod
Dataset : https://paperswithcode.com/dataset/ogb
Paper: https://arxiv.org/abs/2206.10071v1
@ArtificialIntelligencedl
PyGOD is a Python library for graph outlier detection (anomaly detection).
Github: https://github.com/pygod-team/pygod
Dataset : https://paperswithcode.com/dataset/ogb
Paper: https://arxiv.org/abs/2206.10071v1
@ArtificialIntelligencedl
π7