Poster Division to Dates
3.1.2022
| Posters Presenters: |
|---|
| Alon Mamistvalov | Deep Algorithm Unfolding for Sub-Nyquist Ultrasound Imaging |
| Freddy Adiv | Smart Agent Algorithm for Matching Occupations Using Machine Learning |
| Or Bar-Shira | Improved Breast Lesion Characterization via Leaning Based Super Resolution Ultrasound Imaging |
| Oz Frank | A Deep Learning Framework for Analyzing Chest X-Ray and Lung Ultrasound Data with Applications to COVID-19 |
| Iris Kalka | Estimating Heritability of Glycaemic Response to Metformin using Nationwide Electronic Health Records and Population-Sized Pedigree |
| Gili Weiss-Dicker | Unsupervised Particle Sorting for Single-particle Cryo-EM |
| Aviv Navon | Learning the Pareto Front with Hypernetworks |
| Aviv Navon | Auxiliary Learning by Implicit Differentiation |
| Eyal Fishel | CNN-Aided Factor Graphs with Estimated Mutual Information Features for Seizure Detection |
| Guy Revach | KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics |
| Itai Gat | Removing Bias in Multi-modal Classifiers: Regularization by Maximizing Functional Entropies |
| Omri Azencot | A Koopman Approach to Understanding Sequence Neural Models |
| Yuval Belfer | Spectral Analysis of the Neural Tangent Kernel for Deep Residual Networks |
| Aviv Shamsian | Personalized Federated Learning using Hypernetworks |
| Yochai Yemini | Scene-Agnostic Multi-Microphone Speech Dereverberation |
| Alexandra Kogan | Goal-oriented Evidence-based Decision Support Combined with Temporal Reasoning and Multi Criteria Decision Making for Detection and Mitigation of Adverse Events in Multimorbidity Patients |
| Avraham Treistman | Word Embedding Dimensionality Reduction Using Dynamic Variance Thresholding (DyVaT) |
| Alon Shpigler | Inference Graphs for CNN Interpretation |
| Reut Apel | Predicting Decisions in Language Based Persuasion Games |
| Dror Mughaz & Avi Treistman | Word Embedding Dimensionality Reduction Using Dynamic Variance Thresholding (DyVaT) |
4.1.2022
| Posters Presenters: |
|---|
| Amit sofer | Robust Relative Transfer Function Identification on Manifolds for Speech Enhancement |
| Guy Heller | Can Stochastic Gradient Langevin Dynamics Provide Differential Privacy for Deep\\ Learning? |
| Renana Opochinsky | Deep Ranking-Based DOA Tracking Algorithm |
| Chen Amiraz | Distributed Sparse Normal Means Estimation with Sublinear Communication |
| Idan Achituve | GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning |
| Assaf Zaritsky | Solving the "Right" Problems for Effective Machine Learning Driven In Vitro Fertilization |
| Iris Har-Vardi & Assaf Zaritsky | |
| Aviv Zelig | KMD Clustering: Robust Generic Clustering of Biological Data |
| Hila Naaman | Learned ISTA for time encoding FRI Signals |
| Keren Nivasch | A Deep Genetic Method for Keyboard Layout Optimization |
| Nir Shlezinger | Model-Based Deep Learning: Key Approaches and Design Guidelines |
| Rami Nasser | Deep unfolding for non-negative matrix factorization with application to mutational signature analysis |
| Roni Ramon-Gonen | Combined Cluster Analysis and Sequential Pattern Mining Techniques for Disease Evolution Identification in Congestive Heart Failure Patients |
| Tomer Raviv | Meta-ViterbiNet: Online Meta-Learned Viterbi Equalization |
| Armin Shmilovici | Towards Automatic Movie Understanding |
| Shai Elkayam | DeepCRISTL: Deep Transfer Learning Model to Predict Endogeneus On-Target Efficiency of CRISPR/CAS9 Editing |
| Sofia Aizenshtein | Neural Networks for deciphering the amino acid code behind zinc finger protein DNA-binding |
| Maor Turner | Predicting RNA G-quadruplexes From RNA Sequence Using Deep Neural Networks |
| Ori Feldman | Improving the prediction of protein-RNA binding in vivo using experimentally measured RNA structure |
| Reut Moshe | Enhancing the affinity of protein-protein interactions by multiple amino acid mutations predicted by deep neural networks |