Under one protocol, most AI climate models reproduce historical climatology and ENSO response as well as a CMIP6 model, but some underestimate warming trends and all diverge on +2/+4K SST experiments.
A ConvNet for the 2020s, March 2022
21 Pith papers cite this work, alongside 178 external citations. Polarity classification is still indexing.
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background 4representative citing papers
Influpaint uses generative diffusion models on image-encoded influenza data to produce realistic and diverse epidemic trajectories that match leading ensemble methods in accuracy.
Releases the DAPWH dataset of 3556 wasp images including 1739 COCO-annotated examples to enable AI models for identifying Ichneumonoidea and associated families.
ScaleAware-JEPA combines Constrained Diffusion Decomposition with a scale-tied JEPA objective to learn label-free latent coordinates that recover coherent morphology in multiscale fields such as MHD turbulence and interstellar gas.
MICViT outperforms CNN and transformer baselines on brain age prediction from multimodal 3D MRI by combining modality-specific and cross-modal local/global attention across three heterogeneous datasets.
TimeProVe proposes a propose-then-verify framework using lightweight action-based candidate evidence generation followed by targeted VLM verification for efficient long video temporal reasoning, achieving 7.3% improvement on OTB with 75% fewer VLM calls.
JWST measurements of pitch angles in 593 spiral galaxies to z=3.5 show no overall redshift evolution but reveal correlations with mass and sSFR only below z=1.25, implying a transition from locally driven to globally regulated spiral arms.
SynthRAD2025 shows deep learning produces synthetic CTs with MAE 48-65 HU and high dosimetric gamma passing rates for radiotherapy, performing better on CBCT-to-CT than MRI-to-CT tasks.
Exploiting linear structure in VLM embeddings, a synthetic-data pre-training method yields background-invariant representations that exceed 90% worst-group accuracy on Waterbirds even under 100% spurious correlation with no minority examples in training.
A graph-regulated disentangling Mamba model with sparse tokens achieves 93.94% accuracy classifying tree species from MODIS time series in Alberta and outperforms twelve prior models.
Alignment pattern analysis reveals that models aligned to individual brain ROIs do not reproduce the stable cross-region alignment profiles observed across human subjects.
PhysioLite delivers Transformer-comparable ECG/EMG performance using learnable wavelet filters and hardware-aware design at ~370KB quantized size on μNPUs.
ORACLE-2 multimodal classifiers raise macro F1 from 0.52-0.66 (light-curve only) to 0.73 on ZTF Bright Transient Survey data and reach 0.88 on simulated ELAsTiCC data.
SPADE combines sketch-guided path planning with diffusion-augmented imitation learning to achieve better generalization and lower error with fewer parameters than prior methods.
Hist2Style introduces a lightweight bilateral-grid network conditioned on histogram embeddings for distilling large-model stylization into real-time, structure-preserving, user-controllable photorealistic edits.
A physics-informed CNN predicts pore-scale velocity fields from geometry and serves as a warm-start to accelerate Lattice-Boltzmann solvers in over 90% of tested cases.
FedSSG generates and shares synthetic samples within a federated setup to reduce class imbalance and domain shift problems in medical image classification.
HLGFA detects anomalies by identifying breakdowns in cross-resolution feature consistency between high- and low-resolution views of normal samples, guided by structure and detail priors, and reports 97.9% pixel AUROC on MVTec AD.
InternVL scales a vision model to 6B parameters and aligns it with LLMs using web data to achieve state-of-the-art results on 32 visual-linguistic benchmarks.
LETT-NeXt uses RECIST line prompts in a cropped MedNeXt-v2 encoder-decoder to predict 3D lesion masks, reaching DSC 73.9 on hidden test data for a CVPR 2026 segmentation competition.
The NTIRE 2026 challenge reports strong performance from 17 teams on raindrop removal for dual-focused day and night images using an adjusted real-world dataset with 14,139 training images.
citing papers explorer
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AIMIP Phase 1: systematic evaluations of AI weather and climate models
Under one protocol, most AI climate models reproduce historical climatology and ENSO response as well as a CMIP6 model, but some underestimate warming trends and all diverge on +2/+4K SST experiments.
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Generative diffusion models for spatiotemporal influenza forecasting
Influpaint uses generative diffusion models on image-encoded influenza data to produce realistic and diverse epidemic trajectories that match leading ensemble methods in accuracy.
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Descriptor: Parasitoid Wasps and Associated Hymenoptera Dataset (DAPWH)
Releases the DAPWH dataset of 3556 wasp images including 1739 COCO-annotated examples to enable AI models for identifying Ichneumonoidea and associated families.
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ScaleAware-JEPA: Latent Representation for Discovery in Multiscale Physical Fields
ScaleAware-JEPA combines Constrained Diffusion Decomposition with a scale-tied JEPA objective to learn label-free latent coordinates that recover coherent morphology in multiscale fields such as MHD turbulence and interstellar gas.
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Modeling Local, Global, and Cross-Modal Context in Multimodal 3D MRI
MICViT outperforms CNN and transformer baselines on brain age prediction from multimodal 3D MRI by combining modality-specific and cross-modal local/global attention across three heterogeneous datasets.
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TimeProVe: Propose, then Verify for Efficient Long Video Temporal Reasoning in Activities of Daily Living
TimeProVe proposes a propose-then-verify framework using lightweight action-based candidate evidence generation followed by targeted VLM verification for efficient long video temporal reasoning, achieving 7.3% improvement on OTB with 75% fewer VLM calls.
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Spiral arms across cosmic time: JWST measurements of the pitch angles of spiral galaxies at $z<3.5$
JWST measurements of pitch angles in 593 spiral galaxies to z=3.5 show no overall redshift evolution but reveal correlations with mass and sSFR only below z=1.25, implying a transition from locally driven to globally regulated spiral arms.
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Generating synthetic computed tomography for radiotherapy: SynthRAD2025 challenge report
SynthRAD2025 shows deep learning produces synthetic CTs with MAE 48-65 HU and high dosimetric gamma passing rates for radiotherapy, performing better on CBCT-to-CT than MRI-to-CT tasks.
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Birds of a Feather Flock Together: Background-Invariant Representations via Linear Structure in VLMs
Exploiting linear structure in VLM embeddings, a synthetic-data pre-training method yields background-invariant representations that exceed 90% worst-group accuracy on Waterbirds even under 100% spurious correlation with no minority examples in training.
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A Novel Graph-Regulated Disentangling Mamba Model with Sparse Tokens for Enhanced Tree Species Classification from MODIS Time Series
A graph-regulated disentangling Mamba model with sparse tokens achieves 93.94% accuracy classifying tree species from MODIS time series in Alberta and outperforms twelve prior models.
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Only Brains Align with Brains: Cross-Region Alignment Patterns Expose Limits of Normative Models
Alignment pattern analysis reveals that models aligned to individual brain ROIs do not reproduce the stable cross-region alignment profiles observed across human subjects.
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Towards Real-Time ECG and EMG Modeling on $\mu$NPUs
PhysioLite delivers Transformer-comparable ECG/EMG performance using learnable wavelet filters and hardware-aware design at ~370KB quantized size on μNPUs.
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Leveraging Multimodality for Real-Time Classification of Transients and Variables found by the Zwicky Transient Facility
ORACLE-2 multimodal classifiers raise macro F1 from 0.52-0.66 (light-curve only) to 0.73 on ZTF Bright Transient Survey data and reach 0.88 on simulated ELAsTiCC data.
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SPADE: Sketch-guided Path Planning Augmented with Diffusion Experts
SPADE combines sketch-guided path planning with diffusion-augmented imitation learning to achieve better generalization and lower error with fewer parameters than prior methods.
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Hist2Style: Histogram-Guided Stylization with Bilateral Grids
Hist2Style introduces a lightweight bilateral-grid network conditioned on histogram embeddings for distilling large-model stylization into real-time, structure-preserving, user-controllable photorealistic edits.
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Physics-informed convolutional neural networks for fluid flow through porous media
A physics-informed CNN predicts pore-scale velocity fields from geometry and serves as a warm-start to accelerate Lattice-Boltzmann solvers in over 90% of tested cases.
-
Federated Medical Image Classification under Class and Domain Imbalance exploiting Synthetic Sample Generation
FedSSG generates and shares synthetic samples within a federated setup to reduce class imbalance and domain shift problems in medical image classification.
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HLGFA: High-Low Resolution Guided Feature Alignment for Unsupervised Anomaly Detection
HLGFA detects anomalies by identifying breakdowns in cross-resolution feature consistency between high- and low-resolution views of normal samples, guided by structure and detail priors, and reports 97.9% pixel AUROC on MVTec AD.
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InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks
InternVL scales a vision model to 6B parameters and aligns it with LLMs using web data to achieve state-of-the-art results on 32 visual-linguistic benchmarks.
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LETT-NeXt: A Lightweight RECIST-Guided Model for 3D CT Lesion Segmentation
LETT-NeXt uses RECIST line prompts in a cropped MedNeXt-v2 encoder-decoder to predict 3D lesion masks, reaching DSC 73.9 on hidden test data for a CVPR 2026 segmentation competition.
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NTIRE 2026 The Second Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results
The NTIRE 2026 challenge reports strong performance from 17 teams on raindrop removal for dual-focused day and night images using an adjusted real-world dataset with 14,139 training images.