2401.08550] Expanding Hardware-Efficiently Manipulable Hilbert Space via Hamiltonian Embedding Skip to main content We gratefully acknowledge support

2401.08550] Expanding Hardware-Efficiently Manipulable Hilbert Space via Hamiltonian Embedding Skip to main content We gratefully acknowledge support

Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently? Skip to main

of the latent texture. We thoroughly validate TexFusion and show that we can efficiently generate diverse, high quality

this paper, we propose GaussianCity, a generative Gaussian Splatting framework dedicated to efficiently synthesizing unbounded 3D cities

pipeline incorporates powerful VLMs via carefully designed prompts to initialize the annotations efficiently and further

intensive. We introduce the long-context Multi-Modal Sequence Parallelism (MM-SP) system that efficiently parallelizes long video training

However, it remains underexplored how the appearance of such representations can be efficiently edited while maintaining photorealism

the NeRF. Finally, we consider how the hybrid surface-volumetric formulation can be efficiently integrated with a

corresponding to new skeleton poses. We propose a procedural data generation pipeline that efficiently samples training data with

and then compressing visual tokens. This "scale-then-compress" approach enables NVILA to efficiently process high-resolution images

video-to-video translation in order to achieve its goal efficiently. Despite being trained on

validate such attributions. Then, we provide a method for computing these attributions efficiently. Finally, we apply our

estimation. We present a learning-based method that uses normalizing flows to efficiently importance sample illumination product

that independently discretizes each feature dimension, paired with a lightweight autoregressive prediction mechanism that efficiently model the resulting

corresponding to new skeleton poses. We propose a procedural data generation pipeline that efficiently samples training data with

concisely encodes these complex sewing patterns so that LLMs can learn to predict them efficiently. AIpparel achieves state-of

within the hierarchy. This formulation allows the autoregressive model to efficiently capture both spatial and

other authors View PDF Abstract: We show that quantum states with "low stabilizer complexity" can be efficiently distinguished from Haar-random

Teichmann and 3 other authors View PDF Abstract: Retrieving object instances among cluttered scenes efficiently requires compact yet comprehensive

augmented reality. Our model is the first to offer semi-dense matching efficiently, leveraging a novel

i.e., VM) shared among local feature probes, and a basis factor (i.e., M) - efficiently encoding internal relationships and

them to reconstruct a succinct description of the entire state efficiently. Comments: 18 pages, 1

the generated novel view videos to optimize an implicit 4D representation (dynamic NeRF) efficiently, without the need

other authors View PDF Abstract: We give a pair of algorithms that efficiently learn a quantum

experimental) Abstract: We introduce a novel diffusion transformer, LazyDiffusion, that generates partial image updates efficiently. Our approach targets interactive

alignment loss to build an effective conditional GAN-based formulation. E-LatentLPIPS converges more efficiently than many existing distillation

Claude-3.5) to 100%, and explores the environment more efficiently than prior work to

concisely encodes these complex sewing patterns so that LLMs can learn to predict them efficiently. AIpparel achieves state-of

augmented reality. Our model is the first to offer semi-dense matching efficiently, leveraging a novel

Teichmann and 3 other authors View PDF Abstract: Retrieving object instances among cluttered scenes efficiently requires compact yet comprehensive

other authors View PDF Abstract: We give a pair of algorithms that efficiently learn a quantum

them to reconstruct a succinct description of the entire state efficiently. Comments: 18 pages, 1

other authors View PDF Abstract: We show that quantum states with "low stabilizer complexity" can be efficiently distinguished from Haar-random

However, it remains underexplored how the appearance of such representations can be efficiently edited while maintaining photorealism

of SDF. Based on the HDQ algorithm, we leverage sphere tracing to efficiently estimate the surface

introduce a new differentiable mesh processing method that addresses this challenge and efficiently handles meshes with intricate

that vertex and to the nearest pivot. We maintain distances between pivots efficiently by representing them in

environments, we find that nerflets: (1) fit and approximate the scene more efficiently than traditional global NeRFs

the shells whose attributes are encoded in the texture features. These Gaussians are efficiently and differentiably

performance for non-convex optimization. Moreover, QHD is described as a Hamiltonian evolution efficiently simulatable on both digital

introduce a new differentiable mesh processing method that addresses this challenge and efficiently handles meshes with intricate

of SDF. Based on the HDQ algorithm, we leverage sphere tracing to efficiently estimate the surface

alignment loss to build an effective conditional GAN-based formulation. E-LatentLPIPS converges more efficiently than many existing distillation

determine whether there are any other stackable models in KVQ Space that Attention cannot efficiently approximate, which we can

a progressive perception and planning framework, enabling the system to efficiently and robustly

a task. At inference time, each call to the LM is determined by efficiently routing the outcome

experimental) Abstract: We introduce a novel diffusion transformer, LazyDiffusion, that generates partial image updates efficiently. Our approach targets interactive

Claude-3.5) to 100%, and explores the environment more efficiently than prior work to

efficient than model-free RL. How an accurate model can be developed automatically and efficiently from raw sensory inputs

authors View PDF Abstract: We present MVSNeRF, a novel neural rendering approach that can efficiently reconstruct neural radiance fields

in around 0.1s. GRM is a feed-forward transformer-based model that efficiently incorporates multi-view information

neural features, to model a radiance field. Point-NeRF can be rendered efficiently by aggregating neural point

vast number of task instances. Additionally, it algorithmically addresses user queries regarding MLM performance efficiently within a computational

the data points, one can modify the GCV to yield an efficiently-computable unbiased estimator that

neural features, to model a radiance field. Point-NeRF can be rendered efficiently by aggregating neural point

performance for non-convex optimization. Moreover, QHD is described as a Hamiltonian evolution efficiently simulatable on both digital

the shells whose attributes are encoded in the texture features. These Gaussians are efficiently and differentiably

in around 0.1s. GRM is a feed-forward transformer-based model that efficiently incorporates multi-view information

authors View PDF Abstract: We present MVSNeRF, a novel neural rendering approach that can efficiently reconstruct neural radiance fields

HTML (experimental) Abstract: Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In

public, and 2) prior work fails to explore methods for efficiently fine-tuning VLAs for

Stereo Alignment, by Wenyan Cong and 8 other authors View PDF HTML (experimental) Abstract: Efficiently reconstructing 3D scenes from

advances in high-performance numerical simulations of deep quantum circuits to efficiently verify the accuracy

methods in generating high-quality 3D assets with fine-grained textures and materials, efficiently bridging the quality

up networks in ways that aim at utilizing the added computation as efficiently as possible by suitably

Stereo Alignment, by Wenyan Cong and 8 other authors View PDF HTML (experimental) Abstract: Efficiently reconstructing 3D scenes from

and 3 other authors View PDF Abstract: We consider the problem of efficiently computing the derivative

of the above framework based on abstract regularity lemmas. We show how to efficiently implement the regularity

the expert and offline algorithms. Second, we show transformers with ReLU attention can efficiently approximate near-optimal online

for MDPs with multiple reward functions, we develop a planning algorithm that computationally efficiently finds Pareto-optimal stochastic

such as SQA3D (+3.1\%). Taken together, we show that Coarse Correspondences effectively and efficiently boosts models' performance on

feedback from the game, and it remains open how to efficiently learn the EFCE

flexibility. It has the following technical innovations. \textbf{1)} Disco4D learns to efficiently fit the clothing

LLaVA-3D. Leveraging the strong 2D visual understanding priors from LLaVA, our LLaVA-3D efficiently adapts LLaVA for

a new generalizable 3D Gaussian representation approach derived from Multi-View Stereo (MVS) that can efficiently reconstruct unseen scenes. Specifically

eliminating the need for post-processing steps to render novel views efficiently. To effectively

super-resolution models, and can solve inverse problems with conditions applied at different scales efficiently. Comments: Project page: this

PDF Abstract: This paper aims to tackle the challenge of efficiently producing interactive free-viewpoint

super-resolution models, and can solve inverse problems with conditions applied at different scales efficiently. Comments: Project page: this

methods in generating high-quality 3D assets with fine-grained textures and materials, efficiently bridging the quality

Layer Perceptron. The use of spherical Gaussians allows us to efficiently solve for approximate

Supervision (PWS) has emerged as a widespread paradigm to synthesize training labels efficiently. The core

to entities' locations. On the other hand, the progressive dichotomy module can efficiently decode the synthesized

public, and 2) prior work fails to explore methods for efficiently fine-tuning VLAs for

an RGB-only method that leverages color information directly from raw images or video frames. CSCI efficiently captures color-related appearance

Our work highlights the ability of tensor network algorithms to efficiently utilize high-performance GPU

paper deals with giving a detailed description of how to efficiently compute, by means of

to be fast-forwarded, while not necessarily requiring methods that diagonalize the Hamiltonians efficiently. We further develop a

transients, and searches for fast-radio bursts. Gaussian random fields can be sampled efficiently in the

and 2 other authors View PDF Abstract: Weak Supervision (WS) techniques allow users to efficiently create large training datasets

up networks in ways that aim at utilizing the added computation as efficiently as possible by suitably

for MDPs with multiple reward functions, we develop a planning algorithm that computationally efficiently finds Pareto-optimal stochastic

by proposing a data-efficient algorithm based on multi-task reinforcement learning. Our approach efficiently optimizes both physical design

accessibility for underwater robotic intervention operations. SHARC allows multiple remote scientists to efficiently plan and execute

using Anthropic's Claude that LLMs can indeed augment human intelligence to help more efficiently run Polis conversations. In

polynomial-sized emulators exist. We show that they do exist and can be computed efficiently via convex programming. As

configurations in transitive groups, called quandle envelopes. This correspondence allows us to efficiently enumerate connected quandles of

and survey the localized, multiscale transforms that have been proposed to efficiently extract information from high

in the real world. We propose an approach for robots to efficiently learn manipulation skills using