Data-Driven Offline Optimization For Architecting Hardware Accelerators https://arxiv.org/abs/2110.11346
#rl #chips
#rl #chips
Inadequately Pre-trained Models are Better Feature Extractors https://arxiv.org/abs/2203.04668
#cv #feature_extraction
#cv #feature_extraction
Respecting causality is all you need for training physics-informed neural networks https://arxiv.org/abs/2203.07404
#causality #pinn
#causality #pinn
Three things everyone should know about Vision Transformers https://arxiv.org/abs/2203.09795
#cv #vit
#cv #vit
BaGuaLu: Targeting Brain Scale Pretained Models with over 37 Million Cores
https://keg.cs.tsinghua.edu.cn/jietang/publications/PPOPP22-Ma%20et%20al.-BaGuaLu%20Targeting%20Brain%20Scale%20Pretrained%20Models%20w.pdf
#large_scale #moe
https://keg.cs.tsinghua.edu.cn/jietang/publications/PPOPP22-Ma%20et%20al.-BaGuaLu%20Targeting%20Brain%20Scale%20Pretrained%20Models%20w.pdf
#large_scale #moe
Mapping global dynamics of benchmark creation and saturation in artificial intelligence https://arxiv.org/abs/2203.04592
#benchmarks #pwc
#benchmarks #pwc
Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs https://arxiv.org/abs/2203.06717
#cv #cnn
#cv #cnn
In- and out-of-plane field induced quantum spin-liquid states in a more ideal Kitaev material: BaCo2(AsO4)2 https://arxiv.org/abs/2106.13418
#physics #ksl
#physics #ksl
Complex paths around the sign problem https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.94.015006
#physics #mc #sign_problem
#physics #mc #sign_problem
Reviews of Modern Physics
Complex paths around the sign problem
A promising path to solving QCD is on a computer by discretizing spacetime, rewriting the QCD Lagrangian to fit in that discretization, and then taking the appropriate continuum and infinite volume limits. A problem with this method is that the calculation…
Drive&Segment: Unsupervised Semantic Segmentation of Urban Scenes via Cross-modal Distillation https://arxiv.org/abs/2203.11160
#cv #self_supervised #semantic #multimodal
#cv #self_supervised #semantic #multimodal
Kramers-Wannier-like Duality Defects in (3+1)D Gauge Theories https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.128.111601
#physics #topological
#physics #topological
Physical Review Letters
Kramers-Wannier-like Duality Defects in $(3+1)D$ Gauge Theories
We introduce a class of noninvertible topological defects in $(3+1)D$ gauge theories whose fusion rules are the higher-dimensional analogs of those of the Kramers-Wannier defect in the $(1+1)D$ critical Ising model. As in the lower-dimensional case, the presence…
Characterizing and Improving the Robustness of Self-Supervised Learning through Background Augmentations https://arxiv.org/abs/2103.12719
#cv #self_supervised
#cv #self_supervised
A categorical perspective on symmetry, topological
order, and quantum information
https://crdelane.pages.iu.edu/dissertationch1-5.pdf
#physics #category #tqc
order, and quantum information
https://crdelane.pages.iu.edu/dissertationch1-5.pdf
#physics #category #tqc
Superconducting Correlations Out of Repulsive Interactions on a Fractional Quantum Hall Edge https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.122.236802
#physics #qhe
#physics #qhe
Physical Review Letters
Superconducting Correlations Out of Repulsive Interactions on a Fractional Quantum Hall Edge
We consider a fractional quantum Hall bilayer system with an interface between quantum Hall states of filling fractions $({\ensuremath{\nu}}_{\mathrm{top}},{\ensuremath{\nu}}_{\text{bottom}})=(1,1)$ and $(1/3,2)$, motivated by a recent approach to engineering…
U(1) and SU(2) quantum dissipative systems: The Caldeira-Leggett vs. the Amegaokar-Eckern-Schön approaches https://arxiv.org/abs/1508.00807
#physics #dissipation
#physics #dissipation
BIG-bench.pdf
1.6 MB
BIG-bench draft is finally out (compiled from https://github.com/google/BIG-bench/tree/main/docs/paper)
Analysis contribution instructions: https://github.com/google/BIG-bench/blob/main/docs/contributor_instructions.md
#nlp #benchmarks #scaling
Analysis contribution instructions: https://github.com/google/BIG-bench/blob/main/docs/contributor_instructions.md
#nlp #benchmarks #scaling
Forwarded from Machinelearning
🔎 BigDetection: A Large-scale Benchmark for Improved Object Detector Pre-training
Github: https://github.com/amazon-research/bigdetection
Paper: https://arxiv.org/abs/2203.13249v1
Dataset: https://paperswithcode.com/dataset/lvis
@ai_machinelearning_big_data
Github: https://github.com/amazon-research/bigdetection
Paper: https://arxiv.org/abs/2203.13249v1
Dataset: https://paperswithcode.com/dataset/lvis
@ai_machinelearning_big_data
❤1
Capturing Humans in Motion: Temporal-Attentive 3D Human Pose and Shape Estimation from Monocular Video https://arxiv.org/abs/2203.08534
#cv #3d
#cv #3d
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