Poster "representation learning" Papers
137 papers found • Page 1 of 3
Conference
$\mathbb{X}$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs
Vlad Sobal, Mark Ibrahim, Randall Balestriero et al.
A deep inverse-mapping model for a flapping robotic wing
Hadar Sharvit, Raz Karl, Tsevi Beatus
AmorLIP: Efficient Language-Image Pretraining via Amortization
Haotian Sun, Yitong Li, Yuchen Zhuang et al.
A Statistical Theory of Contrastive Learning via Approximate Sufficient Statistics
Licong Lin, Song Mei
A Theoretical Analysis of Self-Supervised Learning for Vision Transformers
Yu Huang, Zixin Wen, Yuejie Chi et al.
A Unifying Framework for Representation Learning
Shaden Alshammari, John Hershey, Axel Feldmann et al.
BiggerGait: Unlocking Gait Recognition with Layer-wise Representations from Large Vision Models
Dingqiang Ye, Chao Fan, Zhanbo Huang et al.
Boosting Multiple Views for pretrained-based Continual Learning
Quyen Tran, Tung Lam Tran, Khanh Doan et al.
Boost Self-Supervised Dataset Distillation via Parameterization, Predefined Augmentation, and Approximation
Sheng-Feng Yu, Jia-Jiun Yao, Wei-Chen Chiu
Can LLMs Reason Over Non-Text Modalities in a Training-Free Manner? A Case Study with In-Context Representation Learning
Tianle Zhang, Wanlong Fang, Jonathan Woo et al.
Closed-Form Training Dynamics Reveal Learned Features and Linear Structure in Word2Vec-like Models
Dhruva Karkada, James Simon, Yasaman Bahri et al.
Connecting Jensen–Shannon and Kullback–Leibler Divergences: A New Bound for Representation Learning
Reuben Dorent, Polina Golland, William (Sandy) Wells
Contextures: Representations from Contexts
Runtian Zhai, Kai Yang, Burak VARICI et al.
Contrastive Learning with Data Misalignment: Feature Purity, Training Dynamics and Theoretical Generalization Guarantees
Jiawei Sun, Shuai Zhang, Hongkang Li et al.
COPER: Correlation-based Permutations for Multi-View Clustering
Ran Eisenberg, Jonathan Svirsky, Ofir Lindenbaum
Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-training of Deep Networks
Siddharth Joshi, Jiayi Ni, Baharan Mirzasoleiman
Deep Kernel Posterior Learning under Infinite Variance Prior Weights
Jorge Loría, Anindya Bhadra
Defining and Discovering Hyper-meta-paths for Heterogeneous Hypergraphs
Yaming Yang, Ziyu Zheng, Weigang Lu et al.
Do Mice Grok? Glimpses of Hidden Progress in Sensory Cortex
Tanishq Kumar, Blake Bordelon, Cengiz Pehlevan et al.
EditCLIP: Representation Learning for Image Editing
Qian Wang, Aleksandar Cvejic, Abdelrahman Eldesokey et al.
Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax
Ivan Butakov, Alexander Semenenko, Alexander Tolmachev et al.
Enhance Multi-View Classification Through Multi-Scale Alignment and Expanded Boundary
Yuena Lin, Yiyuan Wang, Gengyu Lyu et al.
Exploring the Effectiveness of Object-Centric Representations in Visual Question Answering: Comparative Insights with Foundation Models
Amir Mohammad Karimi Mamaghan, Samuele Papa, Karl H. Johansson et al.
Federated Learning with Domain Shift Eraser
Zheng Wang, Zihui Wang, Zheng Wang et al.
Generalization Guarantees for Representation Learning via Data-Dependent Gaussian Mixture Priors
Milad Sefidgaran, Abdellatif Zaidi, Piotr Krasnowski
Geometry of Long-Tailed Representation Learning: Rebalancing Features for Skewed Distributions
Lingjie Yi, Michael Yao, Weimin Lyu et al.
GeSubNet: Gene Interaction Inference for Disease Subtype Network Generation
Ziwei Yang, Zheng Chen, XIN LIU et al.
GreenHyperSpectra: A multi-source hyperspectral dataset for global vegetation trait prediction
Eya Cherif, Arthur Ouaknine, Luke Brown et al.
Group-robust Sample Reweighting for Subpopulation Shifts via Influence Functions
Rui Qiao, Zhaoxuan Wu, Jingtan Wang et al.
Guiding Cross-Modal Representations with MLLM Priors via Preference Alignment
Pengfei Zhao, Rongbo Luan, Wei Zhang et al.
Harnessing Feature Resonance under Arbitrary Target Alignment for Out-of-Distribution Node Detection
Shenzhi Yang, Junbo Zhao, Sharon Li et al.
Holographic Node Representations: Pre-training Task-Agnostic Node Embeddings
Beatrice Bevilacqua, Joshua Robinson, Jure Leskovec et al.
How Classifier Features Transfer to Downstream: An Asymptotic Analysis in a Two-Layer Model
HEE BIN YOO, Sungyoon Lee, Cheongjae Jang et al.
How Far Are We from True Unlearnability?
Kai Ye, Liangcai Su, Chenxiong Qian
Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning
Patrik Reizinger, Siyuan Guo, Ferenc Huszar et al.
Improve Representation for Imbalanced Regression through Geometric Constraints
Zijian Dong, Yilei Wu, Chongyao Chen et al.
Improving Deep Regression with Tightness
Shihao Zhang, Yuguang Yan, Angela Yao
JADE: Joint Alignment and Deep Embedding for Multi-Slice Spatial Transcriptomics
Yuanchuan Guo, Jun Liu, Huimin Cheng et al.
Language Representations Can be What Recommenders Need: Findings and Potentials
Leheng Sheng, An Zhang, Yi Zhang et al.
Latent Zoning Network: A Unified Principle for Generative Modeling, Representation Learning, and Classification
Zinan Lin, Enshu Liu, Xuefei Ning et al.
Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory
Alexander Levine, Peter Stone, Amy Zhang
Learning from Neighbors: Category Extrapolation for Long-Tail Learning
Shizhen Zhao, Xin Wen, Jiahui Liu et al.
Learning View-invariant World Models for Visual Robotic Manipulation
Jing-Cheng Pang, Nan Tang, Kaiyuan Li et al.
Leaving No OOD Instance Behind: Instance-Level OOD Fine-Tuning for Anomaly Segmentation
Yuxuan Zhang, Zhenbo Shi, han ye et al.
Minimal Semantic Sufficiency Meets Unsupervised Domain Generalization
Tan Pan, Kaiyu Guo, Dongli Xu et al.
Mitigating Spurious Features in Contrastive Learning with Spectral Regularization
Naghmeh Ghanooni, Waleed Mustafa, Dennis Wagner et al.
MOCA: Self-supervised Representation Learning by Predicting Masked Online Codebook Assignments
MATTHIEU CORD, Antonin Vobecky, Oriane Siméoni et al.
Morphing Tokens Draw Strong Masked Image Models
Taekyung Kim, Byeongho Heo, Dongyoon Han
Neural Thermodynamics: Entropic Forces in Deep and Universal Representation Learning
Liu Ziyin, Yizhou Xu, Isaac Chuang
OGBench: Benchmarking Offline Goal-Conditioned RL
Seohong Park, Kevin Frans, Benjamin Eysenbach et al.