Papers
11,015 papers found
Deep Encoder, Shallow Decoder: Reevaluating Non-autoregressive Machine Translation
Jungo Kasai, Nikolaos Pappas, Hao Peng et al.
Deep Equals Shallow for ReLU Networks in Kernel Regimes
Alberto Bietti, Francis Bach
Deep Learning meets Projective Clustering
Alaa Maalouf, Harry Lang, Daniela Rus et al.
Deep Networks and the Multiple Manifold Problem
Sam Buchanan, Dar Gilboa, John Wright
Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
Nils Lukas, Yuxuan Zhang, Florian Kerschbaum
Deep Neural Tangent Kernel and Laplace Kernel Have the Same RKHS
Lin Chen, Sheng Xu
Deep Partition Aggregation: Provable Defenses against General Poisoning Attacks
Alexander Levine, Soheil Feizi
Deep Repulsive Clustering of Ordered Data Based on Order-Identity Decomposition
Seon-Ho Lee, Chang-Su Kim
Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients
Brenden K Petersen, Mikel Landajuela Larma, Terrell N. Mundhenk et al.
Deformable DETR: Deformable Transformers for End-to-End Object Detection
Xizhou Zhu, Weijie Su, Lewei Lu et al.
Degree-Quant: Quantization-Aware Training for Graph Neural Networks
Shyam Anil Tailor, Javier Fernandez-Marques, Nicholas Donald Lane
DeLighT: Deep and Light-weight Transformer
Sachin Mehta, Marjan Ghazvininejad, Srinivasan Iyer et al.
Denoising Diffusion Implicit Models
Jiaming Song, Chenlin Meng, Stefano Ermon
Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization
Tatsuya Matsushima, Hiroki Furuta, Yutaka Matsuo et al.
DialoGraph: Incorporating Interpretable Strategy-Graph Networks into Negotiation Dialogues
Rishabh Joshi, Vidhisha Balachandran, Shikhar Vashishth et al.
DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation
Alexandre Rame, Matthieu Cord
Differentiable Segmentation of Sequences
Erik Scharwächter, Jonathan Lennartz, Emmanuel Müller
Differentiable Trust Region Layers for Deep Reinforcement Learning
Fabian Otto, Philipp Becker, Vien Anh Ngo et al.
Differentially Private Learning Needs Better Features (or Much More Data)
Florian Tramer, Dan Boneh
DiffWave: A Versatile Diffusion Model for Audio Synthesis
Zhifeng Kong, Wei Ping, Jiaji Huang et al.
DINO: A Conditional Energy-Based GAN for Domain Translation
Konstantinos Vougioukas, Stavros Petridis, Maja Pantic
Directed Acyclic Graph Neural Networks
Veronika Thost, Jie Chen
Direction Matters: On the Implicit Bias of Stochastic Gradient Descent with Moderate Learning Rate
Jingfeng Wu, Difan Zou, Vladimir Braverman et al.
Disambiguating Symbolic Expressions in Informal Documents
Dennis Müller, Cezary Kaliszyk
Discovering a set of policies for the worst case reward
Tom Zahavy, Andre Barreto, Daniel J Mankowitz et al.