url stringlengths 36 82 | name stringlengths 2 143 | full_name stringlengths 2 143 ⌀ | description stringlengths 0 9.95k | paper dict | introduced_year int64 1.95k 2.02k | source_url stringlengths 32 228 ⌀ | source_title stringlengths 9 170 ⌀ | code_snippet_url stringclasses 464
values | num_papers int64 0 37.4k | collections listlengths 0 6 |
|---|---|---|---|---|---|---|---|---|---|---|
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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{
"area": "Computer Vision",
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}
] |
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{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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{
"area": "Computer Vision",
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}
] |
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{
"area": "Computer Vision",
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{
"area": "Computer Vision",
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}
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{
"area": "Computer Vision",
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{
"area": "General",
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{
"area": "General",
"area_id": "general",
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}
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"title": "WaveMix: Multi-Resolution Token Mixing for Images",
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{
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
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} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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{
"area": "General",
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}
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"title": "Bridging Mini-Batch and Asymptotic Analysis in Contrastive Learning: From InfoNCE to Kernel-Based Losses",
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} | 2,000 | https://arxiv.org/abs/2405.18045v1 | Bridging Mini-Batch and Asymptotic Analysis in Contrastive Learning: From InfoNCE to Kernel-Based Losses | 1 | [
{
"area": "General",
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"collection": "Loss Functions"
}
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{
"area": "Computer Vision",
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"collection": "3D Representations"
}
] | |
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{
"area": "General",
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"collection": "2D Parallel Distributed Methods"
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{
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{
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{
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{
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | 0 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] | |
https://paperswithcode.com/method/can-you-transfer-a-cruise-ticket-to-another-1 | Can you transfer a cruise ticket to another person MSC: ((Passenger Substitution)) | Can you transfer a cruise ticket to another person MSC: ((Passenger Substitution)) | MSC Cruises Name Change Policy+1-855-732-4023 Guide to Passenger Name Corrections & Transfers
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"title": "0-1 phase transitions in sparse spiked matrix estimation",
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} | 2,000 | https://arxiv.org/abs/1911.05030v1 | 0-1 phase transitions in sparse spiked matrix estimation | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/crtracker | CRTracker | CRTracker | CRTracker is an end-to-end cross-view referring multi-object tracking method. | {
"title": "Cross-View Referring Multi-Object Tracking",
"url": "https://paperswithcode.com/paper/cross-view-referring-multi-object-tracking"
} | 2,000 | https://arxiv.org/abs/2412.17807v1 | Cross-View Referring Multi-Object Tracking | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Multi-Object Tracking Models"
}
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https://paperswithcode.com/method/quick-respond-how-do-i-get-response-from | 【Quick_Respond】How do I get response from Delta Airlines? | 【Quick_Respond】How do I get response from Delta Airlines? | To get a response from Delta Airlines, you can use their customer service phone line at 1 (801) 855-5905 or 1 (804) 853-9001, which is available 24/7. You can also try their website's chat feature or reach out on social media (Twitter: @Delta). For specific issues like baggage claims or refund requests, use the relevan... | {
"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
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"title": "0-1 phase transitions in sparse spiked matrix estimation",
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} | 2,000 | https://arxiv.org/abs/1911.05030v1 | 0-1 phase transitions in sparse spiked matrix estimation | null | 0 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 0 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/procrustes | Procrustes | Procrustes | Procrustes | {
"title": "Procrustes registration of two-dimensional statistical shape models without correspondences",
"url": "https://paperswithcode.com/paper/procrustes-registration-of-two-dimensional"
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{
"area": "General",
"area_id": "general",
"collection": "Generalized Linear Models"
}
] |
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"title": "Model-Free Episodic Control",
"url": "https://paperswithcode.com/paper/model-free-episodic-control"
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{
"area": "General",
"area_id": "general",
"collection": "Non-Parametric Regression"
}
] |
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 0 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
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"title": "0-1 phase transitions in sparse spiked matrix estimation",
"url": "https://paperswithcode.com/paper/0-1-phase-transitions-in-sparse-spiked-matrix"
} | 2,000 | https://arxiv.org/abs/1911.05030v1 | 0-1 phase transitions in sparse spiked matrix estimation | null | 0 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
https://paperswithcode.com/method/fope | FoPE | Fourier Position Embedding | {
"title": "Fourier Position Embedding: Enhancing Attention's Periodic Extension for Length Generalization",
"url": "https://paperswithcode.com/paper/fourier-position-embedding-enhancing"
} | 2,000 | https://arxiv.org/abs/2412.17739v3 | Fourier Position Embedding: Enhancing Attention's Periodic Extension for Length Generalization | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "Position Embeddings"
}
] | |
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
https://paperswithcode.com/method/channel-spatial-attention | Channel & Spatial attention | Channel & Spatial attention | Channel & spatial attention combines the advantages of channel attention and spatial attention. It adaptively selects both important objects and regions | {
"title": "Residual Attention Network for Image Classification",
"url": "https://paperswithcode.com/paper/residual-attention-network-for-image"
} | 2,000 | http://arxiv.org/abs/1704.06904v1 | Residual Attention Network for Image Classification | 2 | [
{
"area": "General",
"area_id": "general",
"collection": "Attention Mechanisms"
}
] | |
https://paperswithcode.com/method/how-do-i-update-my-phone-number-in-coinbase-1 | How do I update my phone number in Coinbase Settings? Call +1-833-534-2357 Now! | How do I update my phone number in Coinbase Settings? Call +1-833-534-2357 Now! | If you’re struggling to update your phone +1-833-534-2357 number in Coinbase settings, you’re not alone. Thousands of users face issues when switching to a new number, but the fastest and safest solution is just a call away at +1-833-534-2357. Coinbase relies on your phone for security and two-factor authentication, wh... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
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