Saved in:
| Main Authors: | Singhal, Utkarsh, Xing, Yifei, Yu, Stella X. |
|---|---|
| Format: | Preprint |
| Published: |
2021
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2112.01525 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Learning to Transform for Generalizable Instance-wise Invariance
by: Singhal, Utkarsh, et al.
Published: (2023)
by: Singhal, Utkarsh, et al.
Published: (2023)
Test-Time Canonicalization by Foundation Models for Robust Perception
by: Singhal, Utkarsh, et al.
Published: (2025)
by: Singhal, Utkarsh, et al.
Published: (2025)
VOLTA: The Surprising Ineffectiveness of Auxiliary Losses for Calibrated Deep Learning
by: Ray, Rahul D, et al.
Published: (2026)
by: Ray, Rahul D, et al.
Published: (2026)
Aligning Forest and Trees in Images & Long Captions for Visually Grounded Understanding
by: Woo, Byeongju, et al.
Published: (2026)
by: Woo, Byeongju, et al.
Published: (2026)
Do Generated Data Always Help Contrastive Learning?
by: Wang, Yifei, et al.
Published: (2024)
by: Wang, Yifei, et al.
Published: (2024)
Impact of Layer Norm on Memorization and Generalization in Transformers
by: Singhal, Rishi, et al.
Published: (2025)
by: Singhal, Rishi, et al.
Published: (2025)
Adaptive Sampling of k-Space in Magnetic Resonance for Rapid Pathology Prediction
by: Yen, Chen-Yu, et al.
Published: (2024)
by: Yen, Chen-Yu, et al.
Published: (2024)
Non-negative Contrastive Learning
by: Wang, Yifei, et al.
Published: (2024)
by: Wang, Yifei, et al.
Published: (2024)
Dual-Space Augmented Intrinsic-LoRA for Wind Turbine Segmentation
by: Singhal, Shubh, et al.
Published: (2024)
by: Singhal, Shubh, et al.
Published: (2024)
Residual Kolmogorov-Arnold Network for Enhanced Deep Learning
by: Yu, Ray Congrui, et al.
Published: (2024)
by: Yu, Ray Congrui, et al.
Published: (2024)
Rethinking Multi-domain Generalization with A General Learning Objective
by: Tan, Zhaorui, et al.
Published: (2024)
by: Tan, Zhaorui, et al.
Published: (2024)
DreamSAC: Learning Hamiltonian World Models via Symmetry Exploration
by: Tang, Jinzhou, et al.
Published: (2026)
by: Tang, Jinzhou, et al.
Published: (2026)
IKD+: Reliable Low Complexity Deep Models For Retinopathy Classification
by: Brahmavar, Shreyas Bhat, et al.
Published: (2023)
by: Brahmavar, Shreyas Bhat, et al.
Published: (2023)
Understanding Retrieval-Augmented Task Adaptation for Vision-Language Models
by: Ming, Yifei, et al.
Published: (2024)
by: Ming, Yifei, et al.
Published: (2024)
MEGL: Multimodal Explanation-Guided Learning
by: Zhang, Yifei, et al.
Published: (2024)
by: Zhang, Yifei, et al.
Published: (2024)
Adaptive Negative Evidential Deep Learning for Open-set Semi-supervised Learning
by: Yu, Yang, et al.
Published: (2023)
by: Yu, Yang, et al.
Published: (2023)
DC-DiT: Adaptive Compute and Elastic Inference for Visual Generation via Dynamic Chunking
by: Haridas, Akash, et al.
Published: (2026)
by: Haridas, Akash, et al.
Published: (2026)
Chart Deep Research in LVLMs via Parallel Relative Policy Optimization
by: Tang, Jiajin, et al.
Published: (2026)
by: Tang, Jiajin, et al.
Published: (2026)
Deep Learning in Cardiology
by: Bizopoulos, Paschalis, et al.
Published: (2019)
by: Bizopoulos, Paschalis, et al.
Published: (2019)
On the Geometry of Deep Learning
by: Balestriero, Randall, et al.
Published: (2024)
by: Balestriero, Randall, et al.
Published: (2024)
Pre-Training Meta-Rule Selection Policy for Visual Generative Abductive Learning
by: Jin, Yu, et al.
Published: (2025)
by: Jin, Yu, et al.
Published: (2025)
Measure Twice, Click Once: Co-evolving Proposer and Visual Critic via Reinforcement Learning for GUI Grounding
by: Wang, Wenkai, et al.
Published: (2026)
by: Wang, Wenkai, et al.
Published: (2026)
AsyCo: An Asymmetric Dual-task Co-training Model for Partial-label Learning
by: Li, Beibei, et al.
Published: (2024)
by: Li, Beibei, et al.
Published: (2024)
Real-Time Pill Identification for the Visually Impaired Using Deep Learning
by: Dang, Bo, et al.
Published: (2024)
by: Dang, Bo, et al.
Published: (2024)
DECKBench: Benchmarking Multi-Agent Frameworks for Academic Slide Generation and Editing
by: Jang, Daesik, et al.
Published: (2026)
by: Jang, Daesik, et al.
Published: (2026)
Probing Equivariance and Symmetry Breaking in Convolutional Networks
by: Vadgama, Sharvaree, et al.
Published: (2025)
by: Vadgama, Sharvaree, et al.
Published: (2025)
DeepRepViz: Identifying Confounders in Deep Learning Model Predictions
by: Rane, Roshan Prakash, et al.
Published: (2023)
by: Rane, Roshan Prakash, et al.
Published: (2023)
Reimplementation of Learning to Reweight Examples for Robust Deep Learning
by: Patil, Parth, et al.
Published: (2024)
by: Patil, Parth, et al.
Published: (2024)
Effective Backdoor Mitigation in Vision-Language Models Depends on the Pre-training Objective
by: Verma, Sahil, et al.
Published: (2023)
by: Verma, Sahil, et al.
Published: (2023)
Deep Active Learning in the Open World
by: Xie, Tian, et al.
Published: (2024)
by: Xie, Tian, et al.
Published: (2024)
Possibilistic Predictive Uncertainty for Deep Learning
by: Ni, Yao, et al.
Published: (2026)
by: Ni, Yao, et al.
Published: (2026)
CoUn: Empowering Machine Unlearning via Contrastive Learning
by: Khalil, Yasser H., et al.
Published: (2025)
by: Khalil, Yasser H., et al.
Published: (2025)
PhyCo: Learning Controllable Physical Priors for Generative Motion
by: Narayanan, Sriram, et al.
Published: (2026)
by: Narayanan, Sriram, et al.
Published: (2026)
Learning to Reason Iteratively and Parallelly for Complex Visual Reasoning Scenarios
by: Jaiswal, Shantanu, et al.
Published: (2024)
by: Jaiswal, Shantanu, et al.
Published: (2024)
Are Bias Mitigation Techniques for Deep Learning Effective?
by: Shrestha, Robik, et al.
Published: (2021)
by: Shrestha, Robik, et al.
Published: (2021)
An Overview of Prototype Formulations for Interpretable Deep Learning
by: Li, Maximilian Xiling, et al.
Published: (2024)
by: Li, Maximilian Xiling, et al.
Published: (2024)
Deep Active Learning: A Reality Check
by: Gashi, Edrina, et al.
Published: (2024)
by: Gashi, Edrina, et al.
Published: (2024)
Revisiting Data Augmentation in Deep Reinforcement Learning
by: Hu, Jianshu, et al.
Published: (2024)
by: Hu, Jianshu, et al.
Published: (2024)
Advantages of Neural Population Coding for Deep Learning
by: Hoffmann, Heiko
Published: (2024)
by: Hoffmann, Heiko
Published: (2024)
Lung Cancer Detection Using Deep Learning
by: Ajmi, Imama, et al.
Published: (2026)
by: Ajmi, Imama, et al.
Published: (2026)
Similar Items
-
Learning to Transform for Generalizable Instance-wise Invariance
by: Singhal, Utkarsh, et al.
Published: (2023) -
Test-Time Canonicalization by Foundation Models for Robust Perception
by: Singhal, Utkarsh, et al.
Published: (2025) -
VOLTA: The Surprising Ineffectiveness of Auxiliary Losses for Calibrated Deep Learning
by: Ray, Rahul D, et al.
Published: (2026) -
Aligning Forest and Trees in Images & Long Captions for Visually Grounded Understanding
by: Woo, Byeongju, et al.
Published: (2026) -
Do Generated Data Always Help Contrastive Learning?
by: Wang, Yifei, et al.
Published: (2024)