Jacek Tabor
31 papers · 2018–2026 · 12 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (45) 🌍 Conference Polyglot · Gold 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
🤝
Dynamic Duo
(13)
🏆
Keyword Champion
(2)
🏆
Grand Slam
🧬
Topic Evolution
🌈
Renaissance Researcher
(5)
🔥
Unstoppable · Bronze
⚡
Prolific Year · Productive
💎
Century Club · Bronze
🗃️
Keyword Collector
(148)
Venues
Top co-authors
Research topics
Machine Learning
(22)
Deep Learning
(18)
Artificial Intelligence
(11)
Optimization & Theory
(11)
Core Methods
(10)
Architectures
(8)
Core AI
(7)
Models
(7)
Computer Vision
(6)
Application Areas
(4)
Learning Paradigms
(4)
Learning Types · Machine Learning
(4)
Generation
(3)
Learning Types · Deep Learning
(3)
Techniques
(3)
Keywords
generative model
(3)
image classification
(3)
few-shot learning
(3)
semantic segmentation
(2)
neural network
(2)
matrix factorization
(2)
missing data
(2)
diffusion model
(2)
expected value
(2)
prototypical part
(2)
dynamical isometry
(2)
sparse initialization
(2)
model compression
(2)
low-rank adaptation
(2)
machine unlearning
(2)
bayesian learning
(1)
variational inference
(1)
image generation
(1)
continual learning
(1)
feature learning
(1)
Papers
EPIC: Explanation of Pretrained Image Classification Networks via Prototypes
AAAI 2026
UnGuide: Learning to Forget with LoRA-Guided Diffusion Models
UAI 2026
FreSh: Frequency Shifting for Accelerated Neural Representation Learning
ICLR 2025
GeoGuide: Geometric Guidance of Diffusion Models
WACV 2025
Hypernetwork Approach to Bayesian MAML (Student Abstract)
AAAI 2025
LapSum - One Method to Differentiate Them All: Ranking, Sorting and Top-k Selection
ICML 2025
LucidPPN: Unambiguous Prototypical Parts Network for User-centric Interpretable Computer Vision
ICLR 2025
Minimal Ranks, Maximum Confidence: Parameter-efficient Uncertainty Quantification for LoRA
EMNLP 2025
SEMU: Singular Value Decomposition for Efficient Machine Unlearning
ICML 2025
Face Identity-Aware Disentanglement in StyleGAN
WACV 2024
Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations
AAAI 2024
Sparser, Better, Deeper, Stronger: Improving Static Sparse Training with Exact Orthogonal Initialization
ICML 2024
Bounding Evidence and Estimating Log-Likelihood in VAE
AISTATS 2023
Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training
NeurIPS 2023
HyperShot: Few-Shot Learning by Kernel HyperNetworks
WACV 2023
ProtoSeg: Interpretable Semantic Segmentation With Prototypical Parts
WACV 2023
Revisiting Offline Compression: Going Beyond Factorization-based Methods for Transformer Language Models
EACL 2023
SONGs: Self-Organizing Neural Graphs
WACV 2023
Continual Learning with Guarantees via Weight Interval Constraints
ICML 2022
Interpretable Image Classification with Differentiable Prototypes Assignment
ECCV 2022
LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood
ICML 2022
MisConv: Convolutional Neural Networks for Missing Data
WACV 2022
Direction is what you need: Improving Word Embedding Compression in Large Language Models
ACL 2021
Kernel Self-Attention for Weakly-Supervised Image Classification Using Deep Multiple Instance Learning
WACV 2021
Non-Gaussian Gaussian Processes for Few-Shot Regression
NeurIPS 2021
Zero Time Waste: Recycling Predictions in Early Exit Neural Networks
NeurIPS 2021
Cramer-Wold Auto-Encoder
JMLR 2020
Hypernetwork approach to generating point clouds
ICML 2020
The Break-Even Point on Optimization Trajectories of Deep Neural Networks
ICLR 2020
Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function
AISTATS 2019
Processing of missing data by neural networks
NeurIPS 2018