Avinash Ravichandran

24 papers · 2014–2023 · 5 conferences · across top CS/AI conferences

Achievements

+9 more ↓

🌉 Interdisciplinary Bridge 🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (5) 🏃 Academic Marathon (9) 🗺️ Taxonomy Completionist (52)

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (5) 🤝 Dynamic Duo (21) ⚡ Prolific Year (5) 💎 Century Club (24) 📈 Trend Setter 🔥 Unstoppable (5) 🗃️ Keyword Collector (79)

Conferences

CVPR (10) ICLR (5) NIPS (4) ECCV (3) ICCV (2)

Top co-authors

Stefano Soatto (21) Rahul Bhotika (10) Alessandro Achille (10) Zhaowei Cai (5) Hao Yang (4) Onkar Dabeer (3) Ashwin Swaminathan (3) Yonatan Dukler (3) Gurumurthy Swaminathan (3) Marzia Polito (3)

Keywords

few-shot learning (5) transfer learning (4) image classification (3) vision transformer (3) representation learning (2) self-supervised learning (2) semi-supervised learning (2) semantic segmentation (2) stochastic gradient descent (1) catastrophic forgetting (1) metric learning (1) image segmentation (1) multi-task learning (1) continual learning (1) convex optimization (1) anomaly detection (1) zero-shot learning (1) curriculum learning (1) uncertainty quantification (1) active learning (1)

Papers

Masked Vision and Language Modeling for Multi-modal Representation Learning ICLR 2023 Your representations are in the network: composable and parallel adaptation for large scale models NIPS 2023 Learning Expressive Prompting With Residuals for Vision Transformers CVPR 2023 A Meta-Learning Approach to Predicting Performance and Data Requirements CVPR 2023 WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation CVPR 2023 X-DETR: A Versatile Architecture for Instance-Wise Vision-Language Tasks ECCV 2022 DIVA: Dataset Derivative of a Learning Task ICLR 2022 Rethinking Few-Shot Object Detection on a Multi-Domain Benchmark ECCV 2022 Semi-supervised Vision Transformers at Scale NIPS 2022 Class-Incremental Learning With Strong Pre-Trained Models CVPR 2022 Task Adaptive Parameter Sharing for Multi-Task Learning CVPR 2022 Uniform Sampling over Episode Difficulty NIPS 2021 LQF: Linear Quadratic Fine-Tuning CVPR 2021 Estimating informativeness of samples with Smooth Unique Information ICLR 2021 Exponential Moving Average Normalization for Self-Supervised and Semi-Supervised Learning CVPR 2021 Mixed-Privacy Forgetting in Deep Networks CVPR 2021 Rethinking the Hyperparameters for Fine-tuning ICLR 2020 A Baseline for Few-Shot Image Classification ICLR 2020 Incremental Few-Shot Meta-Learning via Indirect Discriminant Alignment ECCV 2020 Predicting Training Time Without Training NIPS 2020 Meta-Learning With Differentiable Convex Optimization CVPR 2019 Few-Shot Learning With Embedded Class Models and Shot-Free Meta Training ICCV 2019 Task2Vec: Task Embedding for Meta-Learning ICCV 2019 Active Frame, Location, and Detector Selection for Automated and Manual Video Annotation CVPR 2014