Chaim Baskin

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 56

Top Topics

Semantic Attributes

Top Venues

Trans. Mach. Learn. Res.

Publications

Zachary Bamberger, Ofek Glick, Chaim Baskin, Yonatan Belinkov
DEPTH: Discourse Education through Pre-Training Hierarchically. CoRR (2024)
Maor Dikter, Tsachi Blau, Chaim Baskin
Conceptual Learning via Embedding Approximations for Reinforcing Interpretability and Transparency. CoRR (2024)
Moshe Kimhi, David Vainshtein, Chaim Baskin, Dotan Di Castro
Robot Instance Segmentation with Few Annotations for Grasping. CoRR (2024)
Tamir Shor, Chaim Baskin, Alexander M. Bronstein
Leveraging Latents for Efficient Thermography Classification and Segmentation. CoRR (2024)
Eden Grad, Moshe Kimhi, Lion Halika, Chaim Baskin
Benchmarking Label Noise in Instance Segmentation: Spatial Noise Matters. CoRR (2024)
Gabriele Serussi, Tamir Shor, Tom Hirshberg, Chaim Baskin, Alex M. Bronstein
Active propulsion noise shaping for multi-rotor aircraft localization. CoRR (2024)
Moshe Kimhi, Shai Kimhi, Evgenii Zheltonozhskii, Or Litany, Chaim Baskin
Semi-Supervised Semantic Segmentation via Marginal Contextual Information. Trans. Mach. Learn. Res. 2024 (2024)
Klára Janousková, Tamir Shor, Chaim Baskin, Jiri Matas
Single Image Test-Time Adaptation for Segmentation. Trans. Mach. Learn. Res. 2024 (2024)
Moshe Kimhi, Shai Kimhi, Evgenii Zheltonozhskii, Or Litany, Chaim Baskin
Semi-Supervised Semantic Segmentation via Marginal Contextual Information. CoRR (2023)
Tsachi Blau, Roy Ganz, Chaim Baskin, Michael Elad, Alexander M. Bronstein
Classifier Robustness Enhancement Via Test-Time Transformation. CoRR (2023)
Or Feldman, Amit Boyarski, Shai Feldman, Dani Kogan, Avi Mendelson, Chaim Baskin
Weisfeiler and Leman Go Infinite: Spectral and Combinatorial Pre-Colorings. Trans. Mach. Learn. Res. 2023 (2023)
Itay Eilat, Ben Finkelshtein, Chaim Baskin, Nir Rosenfeld
Strategic Classification with Graph Neural Networks. ICLR (2023)
Klára Janousková, Tamir Shor, Chaim Baskin, Jiri Matas
Single Image Test-Time Adaptation for Segmentation. CoRR (2023)
Or Feldman, Chaim Baskin
Leveraging Temporal Graph Networks Using Module Decoupling. CoRR (2023)
Mitchell Keren Taraday, Chaim Baskin
Enhanced Meta Label Correction for Coping with Label Corruption. CoRR (2023)
Mitchell Keren Taraday, Chaim Baskin
Enhanced Meta Label Correction for Coping with Label Corruption. ICCV (2023)
Yaniv Nemcovsky, Evgenii Zheltonozhskii, Chaim Baskin, Brian Chmiel, Alex M. Bronstein, Avi Mendelson
Adversarial robustness via noise injection in smoothed models. Appl. Intell. 53 (8) (2023)
Tom Avrech, Evgenii Zheltonozhskii, Chaim Baskin, Ehud Rivlin
GoToNet: Fast Monocular Scene Exposure and Exploration. CoRR (2022)
Or Feldman, Amit Boyarski, Shai Feldman, Dani Kogan, Avi Mendelson, Chaim Baskin
Weisfeiler and Leman Go Infinite: Spectral and Combinatorial Pre-Colorings. CoRR (2022)
Tom Avrech, Evgenii Zheltonozhskii, Chaim Baskin, Ehud Rivlin
GoToNet: Fast Monocular Scene Exposure and Exploration. J. Intell. Robotic Syst. 105 (3) (2022)
Ben Finkelshtein, Chaim Baskin, Haggai Maron, Nadav Dym
A Simple and Universal Rotation Equivariant Point-Cloud Network. TAG-ML (2022)
Ameen Ali, Tomer Galanti, Evgenii Zheltonozhskii, Chaim Baskin, Lior Wolf
Weakly Supervised Discovery of Semantic Attributes. CLeaR (2022)
Yaniv Nemcovsky, Matan Jacoby, Alex M. Bronstein, Chaim Baskin
Physical Passive Patch Adversarial Attacks on Visual Odometry Systems. ACCV (7) (2022)
Evgenii Zheltonozhskii, Chaim Baskin, Avi Mendelson, Alex M. Bronstein, Or Litany
Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels. WACV (2022)
Itay Eilat, Ben Finkelshtein, Chaim Baskin, Nir Rosenfeld
Strategic Classification with Graph Neural Networks. CoRR (2022)
Moshe Kimhi, Tal Rozen, Tal Kopetz, Olya Sirkin, Avi Mendelson, Chaim Baskin
FBM: Fast-Bit Allocation for Mixed-Precision Quantization. CoRR (2022)
Maxim Fishman, Chaim Baskin, Evgenii Zheltonozhskii, Ron Banner, Avi Mendelson
On Recoverability of Graph Neural Network Representations. CoRR (2022)
Yaniv Nemcovsky, Matan Yaakoby, Alex M. Bronstein, Chaim Baskin
Physical Passive Patch Adversarial Attacks on Visual Odometry Systems. CoRR (2022)
Adam Botach, Evgenii Zheltonozhskii, Chaim Baskin
End-to-End Referring Video Object Segmentation with Multimodal Transformers. CVPR (2022)
Ben Finkelshtein, Chaim Baskin, Haggai Maron, Nadav Dym
A Simple and Universal Rotation Equivariant Point-cloud Network. CoRR (2022)
Tal Rozen, Moshe Kimhi, Brian Chmiel, Avi Mendelson, Chaim Baskin
Bimodal Distributed Binarized Neural Networks. CoRR (2022)
Ben Finkelshtein, Chaim Baskin, Evgenii Zheltonozhskii, Uri Alon
Single-node attacks for fooling graph neural networks. Neurocomputing 513 (2022)
Chaim Baskin, Natan Liss, Eli Schwartz, Evgenii Zheltonozhskii, Raja Giryes, Alex M. Bronstein, Avi Mendelson
UNIQ: Uniform Noise Injection for Non-Uniform Quantization of Neural Networks. ACM Trans. Comput. Syst. 37 (1-4) (2021)
Ameen Ali, Tomer Galanti, Evgeniy Zheltonozhskiy, Chaim Baskin, Lior Wolf
Intersection Regularization for Extracting Semantic Attributes. CoRR (2021)
Evgenii Zheltonozhskii, Chaim Baskin, Avi Mendelson, Alex M. Bronstein, Or Litany
Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels. CoRR (2021)
Adam Botach, Evgenii Zheltonozhskii, Chaim Baskin
End-to-End Referring Video Object Segmentation with Multimodal Transformers. CoRR (2021)
Yury Nahshan, Brian Chmiel, Chaim Baskin, Evgenii Zheltonozhskii, Ron Banner, Alex M. Bronstein, Avi Mendelson
Loss aware post-training quantization. Mach. Learn. 110 (11) (2021)
Chaim Baskin, Brian Chmiel, Evgenii Zheltonozhskii, Ron Banner, Alex M. Bronstein, Avi Mendelson
CAT: Compression-Aware Training for bandwidth reduction. J. Mach. Learn. Res. 22 (2021)
Brian Chmiel, Chaim Baskin, Evgenii Zheltonozhskii, Ron Banner, Yevgeny Yermolin, Alex Karbachevsky, Alex M. Bronstein, Avi Mendelson
Feature Map Transform Coding for Energy-Efficient CNN Inference. IJCNN (2020)
Ben Finkelshtein, Chaim Baskin, Evgenii Zheltonozhskii, Uri Alon
Single-Node Attack for Fooling Graph Neural Networks. CoRR (2020)
Evgenii Zheltonozhskii, Chaim Baskin, Yaniv Nemcovsky, Brian Chmiel, Avi Mendelson, Alex M. Bronstein
Colored Noise Injection for Training Adversarially Robust Neural Networks. CoRR (2020)
Alex Karbachevsky, Chaim Baskin, Evgenii Zheltonozhskii, Yevgeny Yermolin, Freddy Gabbay, Alex M. Bronstein, Avi Mendelson
HCM: Hardware-Aware Complexity Metric for Neural Network Architectures. CoRR (2020)
Evgenii Zheltonozhskii, Chaim Baskin, Alex M. Bronstein, Avi Mendelson
Self-Supervised Learning for Large-Scale Unsupervised Image Clustering. CoRR (2020)
Brian Chmiel, Chaim Baskin, Ron Banner, Evgenii Zheltonozhskii, Yevgeny Yermolin, Alex Karbachevsky, Alexander M. Bronstein, Avi Mendelson
Feature Map Transform Coding for Energy-Efficient CNN Inference. CoRR (2019)
Nir Diamant, Dean Zadok, Chaim Baskin, Eli Schwartz, Alexander M. Bronstein
Beholder-Gan: Generation and Beautification of Facial Images with Conditioning on Their Beauty Level. ICIP (2019)
Chaim Baskin, Brian Chmiel, Evgenii Zheltonozhskii, Ron Banner, Alexander M. Bronstein, Avi Mendelson
CAT: Compression-Aware Training for bandwidth reduction. CoRR (2019)
Yaniv Nemcovsky, Evgenii Zheltonozhskii, Chaim Baskin, Brian Chmiel, Alexander M. Bronstein, Avi Mendelson
Smoothed Inference for Adversarially-Trained Models. CoRR (2019)
Yury Nahshan, Brian Chmiel, Chaim Baskin, Evgenii Zheltonozhskii, Ron Banner, Alexander M. Bronstein, Avi Mendelson
Loss Aware Post-training Quantization. CoRR (2019)
Nir Diamant, Dean Zadok, Chaim Baskin, Eli Schwartz, Alexander M. Bronstein
Beholder-GAN: Generation and Beautification of Facial Images with Conditioning on Their Beauty Level. CoRR (2019)
Yochai Zur, Chaim Baskin, Evgenii Zheltonozhskii, Brian Chmiel, Itay Evron, Alexander M. Bronstein, Avi Mendelson
Towards Learning of Filter-Level Heterogeneous Compression of Convolutional Neural Networks. CoRR (2019)
Chaim Baskin, Natan Liss, Yoav Chai, Evgenii Zheltonozhskii, Eli Schwartz, Raja Giryes, Avi Mendelson, Alexander M. Bronstein
NICE: Noise Injection and Clamping Estimation for Neural Network Quantization. CoRR (2018)
Chaim Baskin, Natan Liss, Evgenii Zheltonozhskii, Alexander M. Bronstein, Avi Mendelson
Streaming Architecture for Large-Scale Quantized Neural Networks on an FPGA-Based Dataflow Platform. IPDPS Workshops (2018)
Chaim Baskin, Eli Schwartz, Evgenii Zheltonozhskii, Natan Liss, Raja Giryes, Alexander M. Bronstein, Avi Mendelson
UNIQ: Uniform Noise Injection for the Quantization of Neural Networks. CoRR (2018)
Natan Liss, Chaim Baskin, Avi Mendelson, Alexander M. Bronstein, Raja Giryes
Efficient non-uniform quantizer for quantized neural network targeting reconfigurable hardware. CoRR (2018)
Chaim Baskin, Natan Liss, Avi Mendelson, Evgenii Zheltonozhskii
Streaming Architecture for Large-Scale Quantized Neural Networks on an FPGA-Based Dataflow Platform. CoRR (2017)
Evgeny Gershikov, Chaim Baskin
Efficient Horizon Line Detection Using an Energy Function. RACS (2017)