research
∙
09/21/2023
Boolformer: Symbolic Regression of Logic Functions with Transformers
In this work, we introduce Boolformer, the first Transformer architectur...
share
research
∙
09/20/2023
Construction of Paired Knowledge Graph-Text Datasets Informed by Cyclic Evaluation
Datasets that pair Knowledge Graphs (KG) and text together (KG-T) can be...
research
∙
06/09/2023
Value function estimation using conditional diffusion models for control
A fairly reliable trend in deep reinforcement learning is that the perfo...
research
∙
06/08/2023
BOOT: Data-free Distillation of Denoising Diffusion Models with Bootstrapping
Diffusion models have demonstrated excellent potential for generating di...
research
∙
06/05/2023
PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model
Autoregressive models for text sometimes generate repetitive and low-qua...
research
∙
04/13/2023
Learning Controllable 3D Diffusion Models from Single-view Images
Diffusion models have recently become the de-facto approach for generati...
research
∙
03/11/2023
Stabilizing Transformer Training by Preventing Attention Entropy Collapse
Training stability is of great importance to Transformers. In this work,...
research
∙
03/07/2023
MAST: Masked Augmentation Subspace Training for Generalizable Self-Supervised Priors
Recent Self-Supervised Learning (SSL) methods are able to learn feature ...
research
∙
02/20/2023
NerfDiff: Single-image View Synthesis with NeRF-guided Distillation from 3D-aware Diffusion
Novel view synthesis from a single image requires inferring occluded reg...
research
∙
10/10/2022
f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation
Diffusion models (DMs) have recently emerged as SoTA tools for generativ...
research
∙
07/27/2022
GAUDI: A Neural Architect for Immersive 3D Scene Generation
We introduce GAUDI, a generative model capable of capturing the distribu...
research
∙
07/05/2022
Efficient Representation Learning via Adaptive Context Pooling
Self-attention mechanisms model long-range context by using pairwise att...
research
∙
02/04/2022
Learning Representation from Neural Fisher Kernel with Low-rank Approximation
In this paper, we study the representation of neural networks from the v...
research
∙
12/02/2021
Robust Robotic Control from Pixels using Contrastive Recurrent State-Space Models
Modeling the world can benefit robot learning by providing a rich traini...
research
∙
09/16/2021
Regularized Training of Nearest Neighbor Language Models
Including memory banks in a natural language processing architecture inc...
research
∙
05/28/2021
An Attention Free Transformer
We introduce Attention Free Transformer (AFT), an efficient variant of T...
research
∙
04/21/2021
MetricOpt: Learning to Optimize Black-Box Evaluation Metrics
We study the problem of directly optimizing arbitrary non-differentiable...
research
∙
06/13/2020
Equivariant Neural Rendering
We propose a framework for learning neural scene representations directl...
research
∙
05/15/2019
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment
In most machine learning training paradigms a fixed, often handcrafted, ...
research
∙
12/22/2016